Systems and methods for homogeneous cargo or payload space reservation with heterogeneous cargos and payloads

ABSTRACT

Methods of determining a final space reservation for a new aircraft are disclosed. The methods include using parametric definitions of potential payloads to generate a population of representative payloads for use in creating an initial space reservation. The methods include accounting for and applying a variety of margins on each potential payload and taking the union of potential payloads. Alternatively, the union can be taken first and then the margins applied. A homogenous space reservation can be determined based upon a variety of differently shaped or sized payloads, including a margin build-up to mitigate risk of unknowns associated with future changes in specific payload shapes and sizes, build tolerances, environmental conditions, and/or loading and unloading motions and clearances. Once this space reservation is known, it is possible to design an external shape of a carrying vehicle by staying outside of this space reservation.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.17/410,660, filed Aug. 24, 2021, which is a U.S. national stage filingfrom International Application Number PCT/US2020/061883, filed Nov. 23,2020, which claims priority to and the benefit of U.S. ProvisionalApplication Ser. No. 62/939,348, filed Nov. 22, 2019, the contents ofeach which is incorporated by reference herein in its entirety.

FIELD

The present disclosure relates to systems and methods for optimallysizing transport-category aircraft and interior cargo bays oftransport-category aircraft capable of moving oversized and multi-objectcargo, although the disclosures can be applied to most any sizeaircraft.

BACKGROUND

Renewable energy remains an increasingly important resourceyear-over-year. While there are many forms of renewable energy, windenergy has increased an average of about 19 percent annually since 2007.The increase in global demand in recent years for more wind energy hascatalyzed drastic advances in wind turbine technology, including thedevelopment of larger, better-performing wind turbines.Better-performing wind turbines can at least sometimes mean largerturbines, as generally turbines with larger rotor diameters can capturemore wind energy. As turbines continue to improve in performance andefficiency, more and more wind farm sites become viable both onshore andoffshore. These sites may be existing sites, where older turbines needreplacement by better-performing, more efficient turbines, and newsites.

A limiting factor to allow for the revitalization of old sites anddevelopment of new sites is transporting the wind turbines, and relatedequipment, to the sites. Wind turbine blades are difficult to transportlong distances due to the terrestrial limitations of existing airvehicles and roadway infrastructures. Onshore transportation hastraditionally required truck or rail transportation on existinginfrastructure. Both are limited by height and width of tunnels andbridges. Road transport has additional complications of lane width, roadcurvature, and the need to pass through urban areas that may requireadditional permitting and logistics, among other complications. Offshoretransportation by ship is equally, if not more so, limiting. Forexample, delivery of parts can be limited to how accessible the offshorelocation is by ship due to various barriers (e.g., sand bars, coralreefs) and the like in the water and surrounding areas, as well as theavailability of ships capable of handling such large structures.

Whether onshore or offshore, the road vehicle or ship options fortransporting such equipment has become more limited, particularly as thesize of wind turbines increase. Delivery is thus limited by theavailability of vehicles and ships capable of handling such largestructures. The very long lengths of wind turbine blades (some arepresently 90 meters long, 100 meters long, or even longer) makeconventional transportation by train, truck, or ship very difficult andcomplicated. Unfortunately, the solution is not as simple as makingtransportation vehicles longer and/or larger. There are a variety ofcomplications that present themselves as vehicles are made longer and/orlarger, including but not limited to complications of: load balancing ofthe vehicle; load balancing the equipment being transported; loadbalancing the two with respect to each other; handling, maneuverability,and control of the vehicle; and other complications that would beapparent to those skilled in the art.

Further, whether onshore or offshore, delivery of parts can be slow andseverely limited by the accessibility of the site. Whether the sitebeing developed is old or new, the sites can often be remote, and thusnot near suitable transportation infrastructure. The sites may be faraway from suitable roads and rails (or other means by which cargo may betransported) to allow for easy delivery of cargo for use in building theturbines at the site and/or other equipment used in developing the site.New sites are often in areas without any existing transportationinfrastructure at all, thus requiring new construction and specialequipment. Ultimately, transportation logistics become cost prohibitive,resulting in a literal and figurative roadblock to further advancing theuse of wind energy on a global scale.

A critical consideration for air vehicle is the required amount of cargospace to reserve for payload. This is true regardless of whether thevehicle carries its cargo internally or externally. If the air vehiclecarries cargo internally, then for any particular nondimensional shapeof the air vehicle, increasing the dimensional size of cargo will resultin a required increase in the size of the air vehicle, which causesincreases in aerodynamic drag, structural weight, and additionaldrag/weight/cost to meet additional requirements for the enclosed volume(e.g., environmental control, ventilation, cargo restraint,crashworthiness, and the like). A nondimensional shape is a term oftenused in aerospace in which a shape has all spatial dimensions anddefining coordinates divided out by a scaling constant that ischaracteristic of the shape. For example, airfoils are often examinednon-dimensionally by considering their shape divided by the chordlength. Simply stated, larger cargo requires an increase in the size ofthe aircraft.

Furthermore, if two or more cargo objects, such as wind turbine blades,are not packaged optimally for transportation, a larger than necessarycargo aircraft will be required for transportation. This results inincreased weight of the aircraft, greater cost to build the aircraft,greater fuel consumption, greater airport restrictions, and the like.Therefore, during the design phase, it is highly desirable to minimizeair vehicle drag, weight, and cost, and to improve air vehicle balance,stability, and controllability by minimizing vehicle dimensions, and byextension, packaged payload dimensions.

The space set aside to carry a cargo or payload is called a spacereservation. If many different types of cargos or payloads are beingconsidered, the final space reservation for all possible combinations ofthese cargos and payloads can be considered a final homogenous spacereservation. Since vehicles and their potential payloads might have avariety of complex shapes and sizes, it is nontrivial to determine thespace reservation for all combinations of sizes and shapes of desiredpayloads and cargos as a starting point for vehicle design.Additionally, the process of earning a fixed-wing aircraft typecertificate is an extremely time-consuming and costly process, generallytaking several years and billions of U.S. dollars after finalization ofa design. By the time an aircraft is designed, prototyped, tested,certified, and produced, significant changes often occur within productsoutside of the aircraft industry. These changes may cause the productsdeveloped in the interim to not fit into aircraft that were originallydeveloped to carry these products. This risk is likely to exist even forvehicles that are not aircraft subject to the type certificationprocess. Once vehicle dimensions are set, a smaller loaded payloadpackage offers a higher likelihood of fitting into the vehicle, plusfaster loading and unloading, more clearance to reduce the likelihood ofcollisions and related damage, and greater accessibility in the loadedcargo bay.

Accordingly, there is a need for ways to calculate the space reservationfor multiple prospective combinations of sizes and shapes of desiredpayloads and cargos as a starting point for vehicle design.

SUMMARY

The present disclosure provides systems and methods for calculating aspace reservation, also referred to herein a “keep-out zone,” based onmultiple prospective combinations of sizes and shapes of desiredpayloads. In some instances, embodiments include generating a parametricmodel of one or more payload types and generating a representativepopulation of payload shapes to determine a maximally sized envelopesuitable to contain all representation population. In some instances,embodiments include determining optimized orientations of multi-objectpayloads of at least some of the representative population of payloadshapes to maximize the packing efficiency before calculating a spacereservation. These and other advantages will be apparent from thefollowing detailed description and accompanying figures.

Examples of the present disclosure include a computer-implemented methodof generating a space reservation volume for use in sizing a cargo bayof a cargo aircraft. The method includes generating one or moreoptimized payload orientations of one or more representative payloads tobe carried in a cargo bay of a cargo aircraft, generating an initialkeep out volume containing the one or more optimized payloadorientations, creating a final keep out volume by sequentially adding aplurality of margins to the initial keep out volume, and generating aspace reservation volume based on the final keep out volume. The threegenerating actions, and the creating action, are performed using aprocessor in at least some instances. The space reservation volume isdimensioned greater than or equal to the final keep out volume such thatthe space reservation volume is suitable for use in sizing interiordimensions of the cargo bay. Further, the cargo bay is suitable for atleast one of loading, unloading, or holding a payload represented by theone or more representative payloads in their respective optimizedpayload orientations.

The one or more representative payloads can include one or more windturbine blades. Generating the initial keep out volume can includegenerating a union of 3D geometries of the one or more optimized payloadorientations. In some examples, generating an initial keep out volumecan include sweeping a 3D geometry of each of the one or morerepresentative payloads in their respective one or more optimizedpayload orientations through at least one of a simulated loadingmovement or a simulated unloading movement to generate a swept 3Dgeometry of a volume swept through by the one or more representativepayloads. It can also include generating a union of the swept 3Dgeometries of the one or more optimized payload orientations.

The method can further include generating one or more optimized payloadorientations of two or more representative payloads by running anoptimization routine configured to test a plurality of possiblenon-intersecting orientations of the two or more representative payloadsand calculate at least one cost function for each possiblenon-intersecting orientation. The optimized payload orientation caninclude a set of possible non-intersecting orientations that: (1)minimizes the one or more cost functions; and/or (2) minimizes aweighted average of the one or more cost functions. Running theoptimization routine to test the plurality of possible non-intersectingorientations of the two or more representative payloads can includekeeping a 3D geometry of at least one of the two or more representativepayloads fixed in space and sequentially iterating a plurality ofdegrees of freedom of the 3D geometries of the remaining two or morerepresentative payloads. Further, for each iteration, the at least onecost function that includes at least a minimum clearance between the twoor more representative payloads can be calculated.

In some examples, the plurality of margins includes a first set ofmargins based on 3D geometries of the one or more representativepayloads. The first set of margins can include at least one or more of:an additive offset for payload shape uncertainty; an additive offset forpayload manufacturing tolerances; an additive offset for payloadflexibility; and/or an additive offset for thermal deformation. Theplurality of margins can include a second set of margins based on 3Dgeometries of one or more fixtures configured to hold the one or morerepresentative payloads in the one or more optimized payloadorientations. The second set can include an additive offset for the oneor more fixtures. In some examples, creating the final keep out volumecan include creating an intermediate keep out volume by sweeping theinitial keep out volume through at least one of a simulated loadingmovement or a simulated unloading movement to generate a third set ofmargins of the plurality of margins based on at least one of the loadingor unloading sweeps. The third set can include an additive offsetrepresenting the volume swept through by the intermediate keep outvolume during the at least one of the simulated loading movement or thesimulated unloading movement.

In some examples, the method includes creating the final keep out volumeby adding one or more of the first or second set of margins to theinitial keep out volume before sweeping the initial keep out volume andsubsequently adding the third set of margins. Creating the final keepout volume can include adding one or more of the first, second, or thirdset of margins to the initial keep out volume after sweeping the initialkeep out volume. In some examples, creating the final keep out volumeincludes adding a fourth set of margins of the plurality of margins, thefourth set including an additive offset representing a minimum clearancemargin between the intermediate keep out volume and an inner wall of thecargo bay. The fourth set can include an additive offset representingmanufacturing tolerances of the cargo aircraft. In some examples, thefourth set includes an additive offset representing structural elementsconfigured to support the one or more representative payloads in thecargo bay. In some examples, the fourth set can include an additiveoffset representing equipment configured to move the one or morerepresentative payloads during a loading operation and/or an unloadingoperation. Generating the space reservation volume can includegenerating a convex hull based on the final keep out volume.

In some examples, the method further includes, before generating the oneor more optimized payload orientations, calculating, for instance usinga processor, the one or more representative payloads by generating 3Dgeometries for a plurality of sample payload shapes when a parameterizednominal payload geometry definition includes a plurality of geometricparameters. Each sample payload shape can have at least one differentgeometric parameter. The method can further include reducing theplurality of sample payload shapes to the one or more representativepayloads using a down-selection process to remove sample payload shapesthat do not expand a volume envelope of a combination of all the samplepayload shapes.

In some examples, generating 3D geometries for a plurality of samplepayload shapes can include using a parametric distribution of one ormore of the plurality of geometric parameters. The parameterized nominalpayload geometry can include a parameterized nominal wind turbinegeometry.

The plurality of geometric parameters can include one or more of thefollowing: a blade twist angle, an airfoil shape, a blade span length, aroot diameter, a cylindrical root length, a root transition length, amaximum chord length, a location of the maximum chord length, athickness at the location of the maximum chord length, a pre-bend tipdeflection, or a pre-sweep tip deflection.

In some examples, the method can include generating a plurality ofdimensions for use in sizing a cargo bay structure to contain the spacereservation volume. In some examples, the method can include generatinga plurality of dimensions for use in sizing a cargo aircraft fuselagestructure to contain, load, and/or unload the space reservation volume.

Another example of the present disclosure is a computer system thatincludes an optimization module, a generating module, a marginingmodule, and a designing module. The optimization module is configured togenerate one or more optimized payload orientations of one or morerepresentative payloads to be carried in a cargo bay of a cargoaircraft. The generating module is configured to generate an initialkeep out volume containing the one or more optimized payloadorientations. The margining module is configured to create a final keepout volume by sequentially adding a plurality of margins to the initialkeep out volume. The designing module is configured to generate a spacereservation volume based on the final keep out volume. The spacereservation volume is dimensioned greater than or equal to the finalkeep out volume such that the space reservation volume is suitable foruse in sizing interior dimensions of the cargo bay and the cargo bay issuitable for at least one of loading, unloading, or holding a payloadrepresented by the one or more representative payloads in theirrespective optimized payload orientations.

The one or more representative payloads can include one or more windturbine blades. The generating module can be further configured togenerate the initial keep out volume by generating a union of 3Dgeometries of the one or more optimized payload orientations. Thegenerating module can be further configured to generate an initial keepout volume by sweeping a 3D geometry of each of the one or morerepresentative payloads in their respective one or more optimizedpayload orientations through at least one of a simulated loadingmovement or a simulated unloading movement to generate a swept 3Dgeometry of a volume swept through by the one or more representativepayloads. Further, the module can be configured to generate a union ofthe swept 3D geometries of the one or more optimized payloadorientations.

The optimization module can be further configured to generate one ormore optimized payload orientations of two or more representativepayloads by running an optimization routine configured to test aplurality of possible non-intersecting orientations of the two or morerepresentative payloads and calculate at least one cost function foreach possible non-intersecting orientation. The optimized payloadorientation can include a set of possible non-intersecting orientationsthat: (1) minimizes the one or more cost functions; and/or (2) minimizesa weighted average of the one or more cost functions.

In some examples, running the optimization routine to test the pluralityof possible non-intersecting orientations of the two or morerepresentative payloads can include keeping a 3D geometry of at leastone of the two or more representative payloads fixed in space andsequentially iterating a plurality of degrees of freedom of the 3Dgeometries of the remaining two or more representative payloads. Foreach iteration, the routine can include calculating the at least onecost function that includes at least a minimum clearance between the twoor more representative payloads. The plurality of margins can include afirst set of margins based on 3D geometries of the one or morerepresentative payloads. The first set of margins can include at leastone or more of: an additive offset for payload shape uncertainty; anadditive offset for payload manufacturing tolerances; an additive offsetfor payload flexibility; and/or an additive offset for thermaldeformation. The plurality of margins can include a second set ofmargins based on 3D geometries of one or more fixtures configured tohold the one or more representative payloads in the one or moreoptimized payload orientations. The second set can include an additiveoffset for the one or more fixtures.

In some examples, the margining module can be further configured tocreate the final keep out volume by creating an intermediate keep outvolume, for instance by sweeping the initial keep out volume through atleast one of a simulated loading movement or a simulated unloadingmovement to generate a third set of margins of the plurality of marginsbased on at least one of the loading or unloading sweeps. The third setcan include an additive offset representing the volume swept through bythe intermediate keep out volume during the at least one of thesimulated loading movement or the simulated unloading movement.

In some examples, the margining module can be further configured tocreate the final keep out volume by adding one or more of the first orsecond set of margins to the initial keep out volume before sweeping theinitial keep out volume and subsequently adding the third set ofmargins. The margining module can be further configured to create thefinal keep out volume by adding one or more of the first, second, orthird set of margins to the initial keep out volume after sweeping theinitial keep out volume. The margining module can be further configuredto create the final keep out volume by adding a fourth set of margins ofthe plurality of margins. The fourth set can include an additive offsetrepresenting a minimum clearance margin between the intermediate keepout volume and an inner wall of the cargo bay. The fourth set caninclude an additive offset representing manufacturing tolerances of thecargo aircraft. The fourth set can include an additive offsetrepresenting structural elements configured to support the one or morerepresentative payloads in the cargo bay. The fourth set can include anadditive offset representing equipment configured to move the one ormore representative payloads during a loading operation and/or anunloading operation. In some examples, the designing module can befurther configured to the create space reservation volume by generatinga convex hull based on the final keep out volume.

Examples of the computer system can include a modeling module. Themodeling module can be configured to, before generating the one or moreoptimized payload orientations, calculate the one or more representativepayloads. The modeling module can further be configured to generate 3Dgeometries for a plurality of sample payload shapes when a parameterizednominal payload geometry definition includes a plurality of geometricparameters Each sample payload shape can have at least one differentgeometric parameter. The modeling module can be further configured toreduce the plurality of sample payload shapes to the one or morerepresentative payloads using a down-selection process to remove samplepayload shapes that do not expand a volume envelope of a combination ofall the sample payload shapes.

In some examples, the modeling module can be further configured togenerate 3D geometries for a plurality of sample payload shapes by usinga parametric distribution of one or more of the plurality of geometricparameters. The parameterized nominal payload geometry can include aparameterized nominal wind turbine geometry.

The plurality of geometric parameters can include one or more of thefollowing: a blade twist angle, an airfoil shape, a blade span length, aroot diameter, a cylindrical root length, a root transition length, amaximum chord length, a location of the maximum chord length, athickness at the location of the maximum chord length, a pre-bend tipdeflection, or a pre-sweep tip deflection. The designing module can befurther configured to generate a plurality of dimensions for use insizing a cargo bay structure to contain the space reservation volume. Insome examples, the designing module can be further configured togenerate a plurality of dimensions for use in sizing a cargo aircraftfuselage structure to contain, load, and/or unload the space reservationvolume.

Yet another example of the present disclosure is a computer programproduct. The computer program product includes a tangible, non-transientcomputer usable medium having computer readable program code on it. Thecomputer readable program code contains instructions that, when executedby a processor, is configured to: (1) generate one or more optimizedpayload orientations of one or more representative payloads to becarried in a cargo bay of a cargo aircraft; (2) generate an initial keepout volume containing the one or more optimized payload orientations;(3) create a final keep out volume by sequentially adding a plurality ofmargins to the initial keep out volume; and (4) generate a spacereservation volume based on the final keep out volume. The spacereservation volume is dimensioned greater than or equal to the finalkeep out volume such that the space reservation volume is suitable foruse in sizing interior dimensions of the cargo bay and the cargo bay issuitable for at least one of loading, unloading, or holding a payloadrepresented by the one or more representative payloads in theirrespective optimized payload orientations.

The one or more representative payloads can include one or more windturbine blades. The instructions to generate the initial keep out volumecan include instruction to generate a union of 3D geometries of the oneor more optimized payload orientations. The instructions to generate aninitial keep out volume can include instructions to sweep a 3D geometryof each of the one or more representative payloads in their respectiveone or more optimized payload orientations through at least one of asimulated loading movement or a simulated unloading movement to generatea swept 3D geometry of a volume swept through by the one or morerepresentative payloads. The instructions to generate can also includeinstructions to generate a union of the swept 3D geometries of the oneor more optimized payload orientations.

The computer program product, in some examples, can include instructionsto generate one or more optimized payload orientations of two or morerepresentative payloads by running an optimization routine configured totest a plurality of possible non-intersecting orientations of the two ormore representative payloads and calculate at least one cost functionfor each possible non-intersecting orientation. The optimized payloadorientation including a set of possible non-intersecting orientationsthat: (1) minimizes the one or more cost functions; and/or (2) minimizesa weighted average of the one or more cost functions.

The computer program product, in some examples, can include instructionsto run the optimization routine to test the plurality of possiblenon-intersecting orientations of the two or more representative payloadsincludes instructions to keep a 3D geometry of at least one of the twoor more representative payloads fixed in space and sequentially iteratea plurality of degrees of freedom of the 3D geometries of the remainingtwo or more representative payloads. For each iteration, the at leastone cost function that includes at least a minimum clearance between thetwo or more representative payloads can be calculated. The plurality ofmargins can include a first set of margins based on 3D geometries of theone or more representative payloads. The first set of margins caninclude at least one or more of: an additive offset for payload shapeuncertainty; an additive offset for payload manufacturing tolerances; anadditive offset for payload flexibility; and/or an additive offset forthermal deformation. The plurality of margins can include a second setof margins based on a 3D geometries of one or more fixtures configuredto hold the one or more representative payloads in the one or moreoptimized payload orientations. The second set can include an additiveoffset for the one or more fixtures.

In some examples, the instructions to create the final keep out volumecan include instructions to create an intermediate keep out volume bysweeping the initial keep out volume through at least one of a simulatedloading movement or a simulated unloading movement to generate a thirdset of margins of the plurality of margins based on at least one of theloading or unloading sweeps. The third set can include an additiveoffset representing the volume swept through by the intermediate keepout volume during the at least one of the simulated loading movement orthe simulated unloading movement.

The computer program product, in some examples, can include instructionsto add one or more of the first or second set of margins to the initialkeep out volume before sweeping the initial keep out volume andsubsequently adding the third set of margins. The computer programproduct, in some examples, can include instructions to add one or moreof the first, second, or third set of margins to the initial keep outvolume after sweeping the initial keep out volume.

The instructions to create the final keep out volume can includeinstructions to add a fourth set of margins of the plurality of margins.The fourth set can include an additive offset representing a minimumclearance margin between the intermediate keep out volume and an innerwall of the cargo bay. The fourth set can include an additive offsetrepresenting manufacturing tolerances of the cargo aircraft. The fourthset can include an additive offset representing structural elementsconfigured to support the one or more representative payloads in thecargo bay. The fourth set can include an additive offset representingequipment configured to move the one or more representative payloadsduring at least one of a loading operation or an unloading operation.

In some examples, the instructions to generate the space reservationvolume can include instructions to generate a convex hull based on thefinal keep out volume.

In some examples, the computer program product of any of claims caninclude, before the instructions to generate the one or more optimizedpayload orientations, instructions to calculate the one or morerepresentative payloads. The instructions can include instructions togenerate 3D geometries for a plurality of sample payload shapes when aparameterized nominal payload geometry definition includes a pluralityof geometric parameters. Each sample payload shape can have at least onedifferent geometric parameter. Further, instructions to reduce theplurality of sample payload shapes to the one or more representativepayloads can use a down-selection process to remove sample payloadshapes that do not expand a volume envelope of a combination of all thesample payload shapes.

The instructions to generate 3D geometries for a plurality of samplepayload shapes can include instructions to use a parametric distributionof one or more of the plurality of geometric parameters. Theparameterized nominal payload geometry can include a parameterizednominal wind turbine geometry. The plurality of geometric parameters caninclude one or more of the following: a blade twist angle, an airfoilshape, a blade span length, a root diameter, a cylindrical root length,a root transition length, a maximum chord length, a location of themaximum chord length, a thickness at the location of the maximum chordlength, a pre-bend tip deflection, or a pre-sweep tip deflection. Thecomputer program product can include instructions to generate aplurality of dimensions for use in sizing a cargo bay structure tocontain the space reservation volume. The computer program product caninclude instructions to generate a plurality of dimensions for use insizing a cargo aircraft fuselage structure to at least one of contain,load, and/or unload the space reservation volume.

Still another example of the present disclosure is an aircraft thatincludes a fuselage defining a forward end, an aft end, a cargo bay thatspans a majority of a length of the fuselage from the forward end to theaft end the interior cargo bay defining an interior volume of a size andshape. The interior volume size and shape are determined by: generatingone or more optimized payload orientations of one or more representativepayloads to be carried in the cargo bay, generating an initial keep outvolume containing the one or more optimized payload orientations,creating a final keep out volume by sequentially adding a plurality ofmargins to the initial keep out volume, and generating the interiorvolume based on the final keep out volume. The size and shape of theinterior volume are dimensioned greater than or equal to the final keepout volume such that the interior volume of the cargo bay is suitablefor at least one of loading, unloading, or holding a payload representedby the one or more representative payloads in their respective optimizedpayload orientations.

BRIEF DESCRIPTION OF DRAWINGS

This disclosure will be more fully understood from the followingdetailed description taken in conjunction with the accompanyingdrawings, in which:

FIG. 1A is an isometric view of one exemplary embodiment of an aircraft;

FIG. 1B is a side view of the aircraft of FIG. 1A;

FIG. 2A is an isometric view of the aircraft of FIG. 1A with a nose conedoor in an open position to provide access to an interior cargo bay ofthe aircraft;

FIG. 2B is an isometric view of the aircraft of FIG. 2A with a payloadbeing disposed proximate to the aircraft for loading into the interiorcargo bay;

FIG. 2C is an isometric, partial cross-sectional view of the aircraft ofFIG. 2B with the payload being partially loaded into the interior cargobay;

FIG. 2D is an isometric, partial cross-sectional view of the aircraft ofFIG. 2C with the payload being fully loaded into the interior cargo bay;

FIG. 3A is a side cross-sectional view of the aircraft of FIG. 1A,including an interior cargo bay of the aircraft;

FIG. 3B is the side cross-sectional view of the aircraft of FIG. 1A withan exemplary payload disposed in the interior cargo bay;

FIG. 4 is a flow chart of one exemplary process of calculating a spacereservation;

FIGS. 5A and 5B are views of a population of representative cargopayloads;

FIG. 5C is a calculated space reservation based on the payloads of FIGS.5A and 5B;

FIG. 6A is an isometric, transparent view of a parametric model of awind turbine blade;

FIG. 6B is a side view of the parametric model of the wind turbine bladeof FIG. 6A;

FIG. 6C is a top view of the parametric model of the wind turbine bladeof FIG. 6A;

FIG. 7A is an isometric view of a plurality of overlappingrepresentative cargo payloads;

FIG. 7B is an isometric view of a union of the plurality of overlappingrepresentative cargo payloads of FIG. 7A;

FIG. 7C is an isometric, semi-transparent view of a union of a pluralityof representative cargo payloads inside of a cargo bay sized accordingto a space reservation calculated using the plurality of representativecargo payloads;

FIG. 8A is an isometric view of one exemplary representative payload andfixture;

FIG. 8B is an isometric view of a schematic illustration of a sweptvolume generated by moving the representative payload and fixture ofFIG. 8A through a loading and/or unloading operation;

FIG. 8C is an illustration showing sides views of an exaggerateddifference between a designed payload shape and an as-built payloadshape;

FIG. 8D is a side view of a schematic illustration of two representativecylinders demonstrating a calculation of a clearance margin;

FIG. 8E is an isometric view of a structural frame of an aircraft cargobay;

FIG. 8F is a schematic cross-section illustration showing theaccumulation of a plurality of margins to determine an interior cargospace reservation and an exterior loft of an aircraft fuselage sectionhaving the interior space reservation;

FIG. 8G is a schematic cross-section illustration of a cargo aircraftholding a payload in a cargo bay;

FIG. 8H is an isometric view of a translucent final keep-out volumeshowing an intermediate keep-out volume and a solid initial keep-outvolume;

FIG. 8I is an isometric view of a solid final keep-out volume disposedinside a translucent exterior loft of an actual aircraft design madeusing the final keep-out volume;

FIG. 9A is scatter plot comparing maximum chord length to blade lengthfor use in a parametric wind turbine blade model;

FIG. 9B is scatter plot comparing prebend to blade length for use in aparametric wind turbine blade model;

FIG. 9C is a scatter plot comparing bolt circle diameter to blade lengthfor use in a parametric wind turbine blade model;

FIG. 9D is a spanwise distribution plot of a plurality of geometricparameters for use in a parametric wind turbine blade model;

FIG. 10A is a YZ plane view of one exemplary embodiment of a bladeenvelop of a parametric model of an 85 m wind turbine blade;

FIG. 10B is an XZ plane view of the blade envelop of the parametricmodel of FIG. 10A;

FIG. 10C is an XY plane view of the blade envelop of the parametricmodel of FIG. 10A;

FIG. 11 is an XY plane view of one exemplary embodiment of a bladeenvelop of a reduced parametric model of an 85-meter wind turbine blade,a 90-meter wind turbine blade, and a 110-meter segmented wind turbineblade;

FIG. 12A is an illustration of two wind turbine blades as examples oftwo highly elongated and irregularly-shaped objects;

FIG. 12B is a schematic illustration of the six degrees of freedom ofthe wind turbine blades of FIG. 12A considered as variables to beadjusted and optimized by the payload orientation optimization routine;

FIG. 13 is an illustration of an optimized orientation of two windturbine blades of FIG. 12A according to an output of a payloadorientation optimization routine based on a minimum clearance costfunction;

FIG. 14A is an illustration of the wind turbine blades of FIG. 12Aarranged according to an optimized payload arrangement;

FIG. 14B is an illustration of the optimized payload arrangement of thewind turbine blades of FIG. 14A inside the interior cargo bay of theaircraft of FIG. 1 ; and

FIG. 15 is a block diagram of one exemplary embodiment of a computersystem for use in conjunction with the present disclosures.

DETAILED DESCRIPTION

Certain exemplary embodiments will now be described to provide anoverall understanding of the principles of the structure, function,manufacture, and use of the devices, systems, aircraft, and methodsdisclosed herein. One or more examples of these embodiments areillustrated in the accompanying drawings. Those skilled in the art willunderstand that the devices, systems, aircraft, components related to orotherwise part of such devices, systems, and aircraft, and methodsspecifically described herein and illustrated in the accompanyingdrawings are non-limiting exemplary embodiments and that the scope ofthe present disclosure is defined solely by the claims. The featuresillustrated or described in connection with one exemplary embodiment maybe combined with the features of other embodiments. Such modificationsand variations are intended to be included within the scope of thepresent disclosure. Some of the embodiments provided for herein may beschematic drawings, including possibly some that are not labeled as suchbut will be understood by a person skilled in the art to be schematic innature. They may not to be scale or may be somewhat crude renderings ofthe disclosed components. A person skilled in the art will understandhow to implement these teachings and incorporate them into work systems,methods, aircraft, and components related to each of the same, providedfor herein.

To the extent the present disclosure includes various terms forcomponents and/or processes of the disclosed devices, systems, aircraft,methods, and the like, one skilled in the art, in view of the claims,present disclosure, and knowledge of the skilled person, will understandsuch terms are merely examples of such components and/or processes, andother components, designs, processes, and/or actions are possible. Byway of non-limiting example, while the present application describesloading an airplane through a front end of the aircraft, alternatively,or additionally, loading can occur through an aft end of the aircraftand/or from above and/or below the aircraft. In the present disclosure,like-numbered and like-lettered components of various embodimentsgenerally have similar features when those components are of a similarnature and/or serve a similar purpose. To the extent terms such asfront, back, top, bottom, forward, aft, proximal, distal, etc. are usedto describe a location of various components of the various disclosures,such usage is by no means limiting, and is often used for conveniencewhen describing various possible configurations. The foregoingnotwithstanding, a person skilled in the art will recognize the commonvernacular used with respect to aircraft, such as the terms “forward”and “aft,” and will give terms of those nature their commonly understoodmeaning. Further in some instances, terms like forward and proximal oraft and distal may be used in a similar fashion.

The present application is directed to systems and methods forcalculating a space reservation volume for use in sizing an interiorcargo bay of a cargo aircraft to load, unload, and transport a class ofnew irregular shapes (e.g., unknown shapes corresponding to future windturbine blades, towers, industrial oil equipment, mining equipment,rockets, military equipment and vehicles, defense hardware, cranesegments, aircraft components, space launch rocket boosters,helicopters, generators, hyperloop tubes, and many other pieces ofoversized cargo). The space reservation volume can represent a keep outzone (e.g., 3D volume and dimensions) for sizing a cargo aircraft and/ora cargo bay of a cargo aircraft suitable for carrying an entire class ofpayload objects having a plurality of different shapes and sizes theirregular shapes together to fit as much as possible into a fixed-sizeinterior cargo bay of an existing air vehicle.

The present disclosure is also related to large, transport-categoryaircraft, capable of moving oversized cargo not traditionally shippableby air. For example, wind turbine blades are irregular in shape and newwind turbine blades are very long (e.g., exceeding 80 meters to 90meters) to provide greater electrical power generating efficiency. Thepresent disclosure provides systems and methods for creating apopulation of representative payload shapes using a parametric model aswell as optimized orientations of multiples of some or all of therepresentative payload shapes using an optimization routine. Theoptimization routine can determine a plurality of packing strategy thatcan be used as an initial representative payload from which to build outa space reservation volume based on a plurality of additive offsets.

Still further, the present disclosure is related to designing interiorcargo bay spaces to best adapt for the optimized packages, thusproviding for optimized interior cargo bay space in addition tooptimized payload packages. Notably, to the extent the presentdisclosures are directed to systems and methods for designing cargo baysof aircrafts, such disclosures can be applied to any vehicle, or anyobject more generally, used in conjunction with holding and/ortransporting a volume, such as trucks, containers (e.g., shippingcontainers), rooms, etc.

Examples of the present disclosure can generate a population of multiplelarge, irregularly-shaped objects, such as wind turbine blades, based ona parametric model and then determine how they may be optimally orientedin space, subject to multiple constraints and cost functions (e.g., aminimum clearance between objects in a payload). The determinations canbe used to generate a plurality of representative payloads, each ofwhich can be swept along a 3D path to simulate a loading and unloadingmovement to generate a swept payload volume. A union can be taken fromthe generated swept payload volume to generate an initial keep-outvolume. Further, once an initial keep-out volume is determined, aplurality of additive offsets can be added to generate a final keep-outvolume that represents the minimum interior cargo bay dimensionsnecessary to load, unload, and transport any real payload that resemblesthe representative payloads (among other payloads).

Example Cargo Aircraft for Carrying Large Irregularly-Shaped Objects

The focus of the present disclosures is described with respect to alarge aircraft 100, such as an airplane, illustrated in FIGS. 1A and 1B,along with the loading of a large payload into the aircraft, illustratedat least in FIGS. 2A-2D. Additional details about the aircraft andpayload may be described with respect to the other figures of thepresent disclosure as well. In the illustrated embodiment, a payload 10is a combination of two wind turbine blades 11A and 11B (FIGS. 2B-2D),although a person skilled in the art will appreciate that other payloadsare possible. Such payloads can include other numbers of wind turbineblades (e.g., one, three, four, five, etc., or segments of a single evenlarger blade), other components of wind turbines (e.g., tower segments,generator, nacelle, gear box, hub, power cables, etc.), or many otherlarge structures and objects whether related to wind turbines or not.The present application can be used in conjunction with most any largepayload—large for the present purposes being at least about 57 meterslong, or at least about 60 meters long, or at least about 65 meterslong, or at least about 75 meters long, or at least about 85 meterslong, or at least about 90 meters long, or at least about 100 meterslong, or at least about 110 meters long, or at least about 120 meterslong—or for smaller payloads if desired. Some non-limiting examples oflarge payloads that can be used in conjunction with the presentdisclosures beyond wind turbines include but are not limited toindustrial oil equipment, mining equipment, rockets, military equipmentand vehicles, defense hardware, commercial aerospace vehicles, cranesegments, aircraft components, space launch rocket boosters,helicopters, generators, or hyperloop tubes. In other words, theaircraft 100 can be used with most any size and shape payload, but hasparticular utility when it comes to large, often heavy, payloads.

As shown, for example in FIGS. 1A-1B and 2A-2D, the aircraft 100, andthus its fuselage 101, includes a forward end 120 and an aft end 140,with a kinked portion 130 connecting the forward end 120 to the aft end140. The forward end 120 is generally considered any portion of theaircraft 100, and related components, that are forward of the kinkedportion 130 and the aft end 140 is considered any portion of theaircraft 100, and related components, that are aft of the kinked portion130. The kinked portion 130, as described in greater detail below, is asection of the aircraft 130 in which both a top-most outer surface 102and a bottom-most outer surface 103 of the fuselage 101 become angled(notably, the placement of reference numerals 102 and 103 in the figuresdo not illustrate location of the “kink” since they more generally referto the top-most and bottom-most surfaces of the fuselage 101), asillustrated by an aft centerline C_(A) of the aft end 140 of thefuselage 101 with respect to a forward centerline C_(F) of the forwardend 120 of the fuselage 101.

The forward end 120 can include a cockpit or flight deck 122, andlanding gears, as shown a forward or nose landing gear 123 and a rear ormain landing gear 124. The illustrated embodiment does not show variouscomponents used to couple the landing gears 123, 124 to the fuselage101, or operate the landing gears (e.g., actuators, braces, shafts,pins, trunnions, pistons, cylinders, braking assemblies, etc.), but aperson skilled in the art will appreciate how the landing gears 123, 124are so connected and operable in conjunction with the aircraft 100. Theforward-most end of the forward end 120 includes a nose cone 126. Asillustrated more clearly in FIG. 2A, the nose cone 126 is functional asa door, optionally being referred to the nose cone door, thus allowingaccess to an interior cargo bay 170 defined by the fuselage 101 via acargo opening 171 exposed by moving the nose cone door 126 into an openor loading position (the position illustrated in FIG. 2A; FIGS. 1A and1B illustrate the nose cone door 126 in a closed or transport position).The door may operate by rotating vertically tip-upwards about a lateralaxis, or by rotating horizontally tip-outboards about a vertical axis,or by other means as well such as translation forwards then in otherdirections, or by paired rotation and translation, or other means.

As described in greater detail below, the interior cargo bay 170 iscontinuous throughout the length of the aircraft 101, i.e., it spans amajority of the length of the fuselage. The continuous length of theinterior cargo bay 170 includes the space defined by the fuselage 101 inthe forward end 120, the aft end 140, and the kinked portion 130disposed therebetween, such spaces being considered corresponding to theforward bay, aft bay, and kinked bay portions of the interior cargo bay170. The interior cargo bay 170 can thus include the volume defined bynose cone 126 when it is closed, as well as the volume defined proximateto a fuselage tail cone 142 located at the aft end 140. In theillustrated embodiment of FIG. 2A, the nose cone door 126 is hinged at atop such that it swings clockwise towards the fuselage cockpit 122 and afixed portion or main section 128 of the fuselage 101. In otherembodiments, a nose cone door can swing in other manners, such as beinghinged on a left or right side to swing clockwise or counter-clockwisetowards the fixed portion 128 of the fuselage. The fixed portion 128 ofthe forwards fuselage 101 is the portion that is not the nose cone 126,and thus the forwards fuselage 101 is a combination of the fixed portion128 and the nose cone 126. Alternatively, or additionally, the interiorcargo bay 170 can be accessed through other means of access known tothose skilled in the art, including but not limited to a hatch, door,and/or ramp located in the aft end 140 of the fuselage 101, hoistingcargo into the interior cargo bay 170 from below, and/or lowering cargointo the interior cargo bay 170 from above. One advantage provided bythe illustrated configuration, at least as it relates to some aspects ofloading large payloads, is that by not including an aft door, theinterior cargo bay 170 can be continuous, making it significantly easierto stow cargo in the aft end 140 all the way into the fuselage tail cone142. While loading through an aft door is possible with the presentdisclosures, doing so would make loading into and use of the interiorcargo bay 170 space in the aft end 140 all the way into the fuselagetail cone 142 much more challenging and difficult to accomplish—alimitation faced in existing cargo aircraft configurations. Existinglarge cargo aircraft are typically unable to add cargo in this way(e.g., upwards and aftwards) because any kink present in their aftfuselage is specifically to create more vertical space for an aft doorto allow large cargo into the forwards portion of the aircraft.

A floor 172 can be located in the interior cargo bay 170, and can alsoextend in a continuous manner, much like the bay 170 itself, from theforward end 120, through the kinked portion 130, and into the aft end140. The floor 172 can thus be configured to have a forward end 172 f, akinked portion 172 k, and an aft end 172 a. In some embodiments, thefloor 172 can be configured in a manner akin to most floors of cargobays known in the art. In some other embodiments, discussed in greaterdetail below, one or more rails can be disposed in the interior cargobay 170 and can be used to assist in loading a payload, such as thepayload 10, into the interior cargo bay 170 and/or used to help securethe location of a payload once it is desirably positioned within theinterior cargo bay 170.

Opening the nose cone 126 not only exposes the cargo opening 171 and thefloor 172, but it also provides access from an outside environment to acantilevered tongue 160 that extends from or otherwise defines aforward-most portion of the fixed portion 128 of the fuselage 101. Thecantilevered tongue can be an extension of the floor 172, or it can beits own feature that extends from below or above the floor 172 andassociated bottom portion of the fuselage 101. The cantilevered tongue160 can be used to support a payload, thus allowing the payload toextend into the volume of the interior cargo bay 170 defined by the nosecone 126.

A wingspan 180 can extend substantially laterally in both directionsfrom the fuselage. The wingspan 180 includes both a first fixed wing 182and a second fixed wing 184, the wings 182, 184 extending substantiallyperpendicular to the fuselage 101 in respective first and seconddirections which are approximately symmetric about alongitudinal-vertical plane away from the fuselage 101, and moreparticularly extending substantially perpendicular to the centerlineC_(F). Wings 182, 184 being indicated as extending from the fuselage 101do not necessarily extend directly away from the fuselage 101, i.e.,they do not have to be in direct contact with the fuselage 101. Further,the opposite directions the wings 182, 184 extend from each other canalternatively be described as the second wing 184 extendingapproximately symmetrically away from the first wing 182. As shown, thewings 182, 184 define approximately no sweep angle and no dihedralangle. In alternative embodiments, a sweep angle can be included in thetip-forwards (−) or tip-aftwards (+) direction, the angle beingapproximately in the range of about −40 degrees to about +60 degrees. Inother alternative embodiments, a dihedral angle can be included in thetip-downwards (negative, or “anhedral”) or tip-upwards (positive, or“dihedral”) direction, the angle being approximately in the range ofabout −5 degrees to about +5 degrees. Other typical components of wings,including but not limited to slats for increasing lift, flaps forincreasing lift and drag, ailerons for changing roll, spoilers forchanging lift, drag, and roll, and winglets for decreasing drag can beprovided, some of which a person skilled in the art will recognize areillustrated in the illustrations of the aircraft 100 (other parts ofwings, or the aircraft 100 more generally, not specifically mentioned inthis detailed description are also illustrated and recognizable by thoseskilled in the art). Engines, engine nacelles, and engine pylons 186 canalso be provided. In the illustrated embodiment, two engines 186, onemounted to each wing 182, 184 are provided. Additional engines can beprovided, such as four or six, and other locations for engines arepossible, such as being mounted to the fuselage 101 rather than thewings 182, 184.

The kinked portion 130 provides for an upward transition between theforward end 120 and the aft end 140. The kinked portion 130 includes akink, i.e., a bend, in the fixed portion 128 of the fuselage 101 suchthat both the top-most outer surface 102 and the bottom-most outersurface 103 of the fuselage 101 become angled with respect to thecenterline C_(F) of the forward end 120 of the aircraft 100, i.e., bothsurfaces 102, 103 include the upward transition provided for by thekinked portion 130. As shown at least in FIG. 1B, the aft-most end ofthe aft end 140 can raise entirely above the centerline C_(F). In theillustrated embodiment, the angle defined by the bottom-most outersurface 103 and the centerline C_(F) is larger than an angle defined bythe top-most outer surface 102 and the centerline C_(F), although otherconfigurations may be possible. Notably, although the present disclosuregenerally describes the portions associated with the aft end 140 asbeing “aft,” in some instances they may be referred to as part of a“kinked portion” or the like because the entirety of the aft end 140 isangled as a result of the kinked portion 130. Thus, references herein,including in the claims, to a kinked portion, a kinked cargo bay orcargo bay portion, a kinked cargo centerline, etc. will be understood bya person skilled in the art, in view of the present disclosures, to bereferring to the aft end 140 of the aircraft 100 (or the aft end inother aircraft embodiments) in some instances.

Despite the angled nature of the aft end 140, the aft end 140 iswell-suited to receive cargo therein. In fact, the aircraft 100 isspecifically designed in a manner that allows for the volume defined bythe aft end 140, up to almost the very aft-most tip of the aft end 140,i.e., the fuselage tail cone 142, can be used to receive cargo as partof the continuous interior cargo bay 170. Proximate to the fuselage tailcone 142 can be an empennage 150, which can include horizontalstabilizers for providing longitudinal stability, elevators forcontrolling pitch, vertical stabilizers for providinglateral-directional stability, and rudders for controlling yaw, amongother typical empennage components that may or may not be illustratedbut would be recognized by a person skilled in the art.

The aircraft 100 is particularly well-suited for large payloads becauseof a variety of features, including its size. A length from theforward-most tip of the nose cone 126 to the aft-most tip of thefuselage tail cone 142 can be approximately in the range of about 60meters to about 150 meters. Some non-limiting lengths of the aircraft100 can include about 80 meters, about 84 meters, about 90 meters, about95 meters, about 100 meters, about 105 meters, about 107 meters, about110 meters, about 115 meters, or about 120 meters. Shorter and longerlengths are possible. A volume of the interior cargo bay 170, inclusiveof the volume defined by the nose cone 126 and the volume defined in thefuselage tail cone 142, both of which can be used to stow cargo, can beapproximately in the range of about 1200 cubic meters to about 12,000cubic meters, the volume being dependent at least on the length of theaircraft 100 and an approximate diameter of the fuselage (which canchange across the length). One non-limiting volume of the interior cargobay 170 can be about 6850 cubic meters. Not accounting for the veryterminal ends of the interior cargo bay 170 where diameters get smallerat the terminal ends of the fuselage 101, diameters across the length ofthe fuselage, as measured from an interior thereof (thus defining thevolume of the cargo bay) can be approximately in the range of about 4.3meters to about 13 meters, or about 8 meters to 11 meters. Onenon-limiting diameter of the fuselage 101 proximate to its midpoint canbe about 9 meters. The wingspan, from tip of the wing 132 to the tip ofthe wing 134, can be approximately in the range of about 60 meters to110 meters, or about 70 meters to about 100 meters. One non-limitinglength of the wingspan 180 can be about 80 meters. A person skilled inthe art will recognize these sizes and dimensions are based on a varietyof factors, including but not limited to the size and mass of the cargoto be transported, the various sizes and shapes of the components of theaircraft 100, and the intended use of the aircraft, and thus they are byno means limiting. Nevertheless, the large sizes that the presentdisclosure both provides the benefit of being able to transport largepayloads, but faces challenges due, at least in part, to its size thatmake creating such a large aircraft challenging. The engineeringinvolved is not merely making a plane larger. As a result, manyinnovations tied to the aircraft 100 provided for herein, and in othercounterpart patent applications, are the result of very specific designsolutions arrived at by way of engineering.

Materials typically used for making fuselages can be suitable for use inthe present aircraft 100. These materials include, but are not limitedto, metals and metal alloys (e.g., aluminum alloys), composites (e.g.,carbon fiber-epoxy composites), and laminates (e.g., fiber-metalliclaminates), among other materials, including combinations thereof.

FIGS. 2B-2D provide for a general, simplified illustration of oneexemplary embodiment of loading a large payload 10 into the aircraft100. As shown, the cargo nose door 126 is swung upwards into its openposition, exposing the portion of the interior cargo bay 170 associatedwith the fixed portion 128 of the fuselage 101, which can extend throughthe kinked portion 130 and through essentially the entirety of the aftend 140. The cargo opening 171 provides access to the interior cargo bay170, and the cantilevered tongue 160 can be used to help initiallyreceive the payload. As shown, the payload 10 includes two wind turbineblades 11A, 11B, held with respect to each other by payload-receivingfixtures 12. The payload-receiving fixtures 12 are generally consideredpart of the payload, although in an alternative interpretation, thepayload 10 can just be configured to be the blades 11A, 11B. Thispayload 10 can be considered irregular in that the shape, size, andweight distribution across the length of the payload is complex, causinga center of gravity of the payload to be at a separate location than ageometric centroid of the payload. One dimension (length) greatlyexceeds the others (width and height), the shape varies with complexcurvature nearly everywhere, and the relative fragility of the payloadrequires a minimum clearance be maintained at all times as well asfixturing support the length of the cargo at several locations evenunder the payload's own weight under gravity. Additional irregularpayload criteria can include objects with profiles normal to alengthwise axis rotate at different stations along that axis, resultingin a lengthwise twist (e.g., wind turbine blade spanwise twist) orprofiles are located along a curved (rather than linear) path (e.g.,wind turbine blade in-plane sweep). Additionally, irregular payloadsinclude objects where a width, depth, or height vary non-monotonicallyalong the length of the payload (e.g., wind turbine blade thickness canbe maximal at the max chord station, potentially tapering to a smallercylinder at the hub and to a thin tip). The term irregular package willbe similarly understood.

The payload 10, which can also be referred to as a package, particularlywhen multiple objects (e.g., more than one blade, a blade(s) andballast(s)) are involved, possibly secured together and manipulated as asingle unit, can be delivered to the aircraft 100 using most anysuitable devices, systems, vehicles, or methods for transporting a largepayload on the ground. A package can involve a single object though. Inthe illustrated embodiment, a transport vehicle 20 includes a pluralityof wheeled mobile transporters 22 linked together by a plurality ofspans, as shown trusses 24. In some instances, one or more of thewheeled mobile transporters 22 can be self-propelled, or the transportvehicle 20 more generally can be powered by itself in some fashion.Alternatively, or additionally, an outside mechanism can be used to movethe vehicle 20, such as a large vehicle to push or pull the vehicle 20,or various mechanical systems that can be used to move large payloads,such as various combinations of winches, pulleys, cables, cranes, and/orpower drive units.

As shown in FIG. 2B, the transport vehicle 20 can be driven or otherwisemoved to the forward end 120 of the aircraft 100, proximate to the cargoopening 171. Subsequently, the payload 10 can begin to be moved from thetransport vehicle 20 and into the interior cargo bay 170. This canlikewise be done using various combinations of one or more winches,pulleys, cables, cranes, and/or power drive units, such set-ups andconfigurations being known to those skilled in the art. FIG. 2Cillustrates a snapshot of the loading process with half of the fuselageremoved for illustrative purposes (as currently shown, the half of thenose cone 126 illustrated is in both an open and closed position, butduring loading through the cargo opening 171, it is in an openposition). As shown, the payload 10 is partially disposed in theinterior cargo bay 170 and is partially still supported by the transportvehicle 20. A distal end 10 d of the payload 10 is still disposed in theforward end 120, as it has not yet reached the kinked portion 130.

The system and/or methods used to move the payload 10 into the partiallyloaded position illustrated in FIG. 2C can continue to be employed tomove the payload 10 into the fully loaded position illustrated in FIG.2D. As shown, the distal end 10 d of the payload 10 d is disposed in theinterior cargo bay 170 at the aft end 140, a proximal end 10 p of thepayload 10 is disposed in the interior cargo bay 170 at the forward end120 (for example, on the cantilevered tongue 160, although the tongue isnot easily visible in FIG. 2D), and the intermediate portion of thepayload 10 disposed between the proximal and distal ends 10 p, 10 dextends from the forward end 120, through the kinked portion 130, andinto the aft end 140. As shown, the only contact points with a floor ofthe interior cargo bay 170 (which for these purposes includes the tongue160) are at the proximal and distal ends 10 p, 10 d of the payload 10and at two intermediate points 10 j, 10 k between the proximal anddistal ends 10 p, 10 d, each of which is supported by a correspondingfixture 12. In other embodiments, there may be fewer or more contactpoints, depending, at least in part, on the size and shape of each ofthe payload and related packaging, the size and shape of the cargo bay,the number of payload-receiving fixture used, and other factors. Thisillustrated configuration of the payload disposed in the interior cargobay 170 is more clearly understood by discussing the configuration ofthe kinked fuselage (i.e., the fuselage 101 including the kinked portion130) in greater detail. Once the payload 10 is fully disposed in theinterior cargo bay 170, it can be secured within the cargo bay 170 usingtechniques provided for herein, in counterpart applications, orotherwise known to those skilled in the art.

FIG. 3A is side cross-section view of the cargo aircraft 100, thecross-section being taken along an approximate midline T-T of thetop-most outer surface, as shown in FIG. 1A. The cargo bay 170 defines acenterline that extends along the overall length of the cargo bay 170.The cargo bay 170 extends from a forward end 171 of a forward end orregion 170 f of the cargo bay 170, as shown located in the nose cone126, to an aft end 173 of an aft end or region 170 a of the cargo bay170, as shown located in the fuselage tail cone 142. The forward and aftregions 170 f, 170 a of the cargo bay 170 sit within the forward and aftends 120, 140, respectively, of the aircraft 100. More particularly, theforward region 170 f can generally define a forward cargo centerlineC_(FCB) that can be substantially colinear or parallel to the forwardfuselage centerline C_(F) (shown in FIG. 4 ) and the aft region 170 acan generally define an aft cargo centerline C_(ACB) that can besubstantially colinear or parallel to the aft fuselage centerline C_(A)(shown in FIG. 4 ). Accordingly, in the kinked portion 130 of thefuselage 101, which itself can include a comparable kinked portion 170 kof the cargo bay 170, where the aft fuselage centerline C_(A) bends withrespect to the forward fuselage centerline C_(F), the aft cargocenterline C_(ACB) also bends at a kink location 631 with respect to theforward cargo centerline C_(FCB). The bend can be at approximately thesame angle, as shown an angle α_(100KP), as the kink angle α_(100K) ofthe fuselage 101. The aft cargo centerline C_(ACB) can extend at leastapproximately 25% of a length of a centerline of the continuous interiorcargo bay 170, i.e., the length of the centerline throughout the entirecargo bay 170. This amount more generally can be approximately in therange of about 25% to about 50%. There are other ways to describe thesedimensional relationships as well, including, by way of non-limitingexample, a length of the aft cargo centerline C_(ACB) being at leastapproximately 45% of the length of the fuselage 101 and/or at leastapproximately 80% of a length of the fuselage 101 aft of the lateralpitch axis, among other relationships provided for herein or otherwisederivable from the present disclosures.

FIG. 3A shows the aft region 170 a of the cargo bay 170 extendingthrough almost all of the aft fuselage 140, which is a distinctadvantage of the configurations discussed herein. Moreover, due to thelength of the aft fuselage 140, a pitch 674 of structural frames 104 aof the aft fuselage 140 can be angled with respect to a pitch 672 ofstructural frames 104 f of the forward fuselage 120 approximately equalto the kink angle α_(100K) of the fuselage 101. In some examples, thekinked region 130 represents an upward transition between the pitch 672of the structural frames 104 f of the forward fuselage 120 and the pitch674 of the structural frames 104 a of the aft fuselage 140. A personskilled in the art will recognize that structural frames 104 a, 104 fare merely one example of structural features or elements that can beincorporated into the fuselage 101 to provide support. Such elements canbe more generally described as circumferentially-disposed structuralelements that are oriented orthogonally along the aft centerline C_(ACB)and the forward centerline C_(FCB). In some examples, the location ofthe cargo bay kink 631 is forward or aft of a fuselage kink such thateither the forward cargo region 170 f partially extends into the aftfuselage 140 or the aft cargo region 170 a partially extends into theforward fuselage 120, however, this generally depends, at least in part,on the distance between the interior of the cargo bay 170 and theexterior of the fuselage, which is typically a small distance for cargoaircraft having a maximally sized cargo bay. Regardless, to fullyutilize examples of the present disclosure, the aft region 170 a of thecargo bay 170 can be both (1) able to be substantially extended due tothe ability of the aft fuselage 140 length to be extended and (2) ableto extend along substantially all of the length of the aft fuselage 140because examples of the present disclosure enable aircraft to haveelongated aft fuselages for a fixed tailstrike angle and/or minimizedkink angle. Additionally, minimizing the fuselage kink angle forelongated aft fuselages allows the aft region of the cargo bay to extendfurther along the fuselage while increasing the maximum straight-linepayload length for a given overall aircraft length and tailstrike angle,as shown at least in FIG. 3B.

FIG. 3B shows a side cross-sectional view of the fuselage 101 of thecargo aircraft 100 of FIG. 1A with a highly elongated payload 10 of twowind turbine blades 11A, 11B disposed substantially throughout theinterior cargo bay 170 and extending from the forward end 171 of theforward region 170 f to the aft end 173 of the aft region 170 a. Havingat least a portion of the aft region 170 a being linearly connected to(e.g., within line of sight) of at least a portion of the forward region170 f enables the extension of the aft region 170 a to result in anextension in the maximum overall length of a rigid payload capable ofbeing carried inside the interior cargo bay 170. Wind turbine blades,however, are often able to be deflected slightly during transport and soexamples of the present disclosure are especially suited to theirtransport as the ability to slightly deflect the payload 10 duringtransport enables even long maximum payload lengths to be achieved byfurther extending the aft end 173 of the aft region 170 a beyond theline of sight of the forward-most end 171 of the forward region 170 f.

Additional details about a kinked fuselage configuration may be providedin International Patent Application No. PCT/US2020/049787, entitled“AIRCRAFT FUSELAGE CONFIGURATIONS FOR AVOIDING TAIL STRIKE WHILEALLOWING LONG PAYLOADS,” and filed Sep. 8, 2020, and the content ofwhich is incorporated by reference herein in its entirety.

Space Reservation Systems and Methods

The present disclosure is related to large, transport-category aircraftcapable of moving oversized cargo not traditionally shippable by air(and potentially, among other uses, future cargo that is not shippableat higher levels of assembly by any current means). The presentdisclosure describes a process to determine a final space reservationfor a new cargo vehicle based upon, at least in some embodiments,defining parametric definitions of potential desired payloads,accounting for and applying a variety of margins on each potentialdesired payload, and then determining the union of all potential desiredpayloads. The context of the space reservation systems and methodsdisclosed herein are framed using the example of wind turbine bladestransported by a fixed-wing aircraft, however, the present disclosure isequally applicable to designing vehicles or other objects to carry anytype of new or uncertain cargo.

As discussed above, the space set aside to carry a cargo or payload iscalled a space reservation. Determining a space reservation for allcombinations of sizes and shapes of desired payloads and cargos as astarting point for vehicle design is a nontrivial process. The flowchartof FIG. 4 illustrates a new approach for easing this process. Itinvolves a unique way of determining a required final homogenous spacereservation for all potential desired payloads or cargos for a newvehicle including a variety of margins. The process starts with one ormore representative payload objects (e.g., representing an entire rangeof sizes and shapes of one or more classes of objects, a known group ofobjects, or just a single object) and takes into account a variety ofparameters, discussed in more detail herein, to generate a finalkeep-out zone (e.g., a space reservation) for use in sizing an aircraftor vehicle for loading, unloading, and transporting all of the potentialdesired payloads.

The process can begin at step 410 by determining the population of allpotential desired payload types, for example wind turbine blades between70 meters and 110 meters in length. Next, if shapes and sizes of thepopulation are not all known (e.g., to account for future designs) atstep 420, a parametric model for the desired payload types can bedeveloped, and then, at step 430, ranges for each geometric parameter ofthe parametric model can be estimated based on known information (e.g.,expected trends) to, at step 440, generate a population ofrepresentative payload objects suitable for use in designing an aircraftor vehicle to carry all of the potential real payload objects (and, ifdesired, combinations thereof) represented by the population.

For example, if a design objective is a vehicle to carry all single unitwind turbine blades up to 90 meters in length, a parametric model ofwind turbine blades is then developed and ranges for the variousparameters are estimated for blades up to 90 meters, from which apopulation of representative payload objects (e.g., a group of 85 meterand 90 meter blades) can be generated. Each payload object of theplurality can have some maximum or minimum dimension such that if avehicle is be sized to carry all of the population of representativepayload objects, it is anticipated that the vehicle can be used totransport any current or future wind turbine blade that is 90 meters inlength or shorter. Additionally, as an optional step, payloads thatinclude multiple objects of the population of individual payload objectscan be considered as well. Additionally, when sizing for payloads thatinclude two or more payload objects, an additional step of determiningoptimized arrangements of two or more payload objects can also be usedto find optimized orientations to be used in the sizing along with anyindividual payload objects of the plurality. To continue the example,this would be sizing a vehicle for all individual wind turbine bladesunder 90 meters as well as optimized combination of two wind turbineblades under 80 meters, or some other value less than 90 meters.

With a population of representative payloads, a down-selections step 441can be conducted to reduce the population to a only those payloads thatrepresent some outer bound of a geometric volume containing all of thepayloads (e.g., only those that would substantively change the resultdesign of a cargo volume configured to carry the population.Additionally, an optimization step 442 can be used to determine anoptimal orientation of each of the payloads to, for example, allow anoptimized overlapping of each payload to be used when making a union ofall the payloads and to reduce any space that may be wasted when groupsof two or more payload objects are being considered as representativepayloads (e.g., two or more payload objects whose geometries present anon-trivial problem of determining their optimal respective orientationsfor being carried in an efficiently-sized cargo volume). Both of thesteps 441, 442 can be performed in a variety of manners, including butnot limited to those disclosed herein or otherwise derivable from thepresent disclosures, without departing from the spirit of the presentdisclosure.

Next a plurality of margins can be calculated at step 450 to account fora plurality of different tolerances and clearances required, such as dueto the manufacture of the payloads or vehicle or the expecteddeformations of the payloads due to flight loads. Additionally, loadingand unloading paths for the payloads can be considered by sweeping eachpayload through an unloading and unloading path to generate a sweptvolume before adding the plurality of margins at step 460. With eachpayload volume or swept payload volume being margined, a union of allmargined payloads is generated at step 470. If the margins added wereconfigured to only account for the payload and any interior constraintsof a cargo bay, the union can be simplified and used for sizing aninterior cargo bay volume at step 481. Alternatively, additional marginscan be applied to account for various structural aspects of the vehiclesuch that the union can be simplified and used for generating an entireexterior vehicle section, such as an external skin of a fuselage sectionof an aircraft containing a cargo bay configured to carry the entirepopulation of representative payloads.

FIGS. 5A and 5B illustrate a population of representative cargo payloadsand FIG. 5C illustrates a calculated space reservation based on therepresentative cargo payloads. In FIG. 5A, the representative payloadsinclude differently sized and shaped individual wind turbine blades 501,502, 503, while in FIG. 5B there are three different payloadarrangements 511, 513, 514 of multiple wind turbine blades. Moreparticularly, the illustrated first payload arrangement 511 includes afirst pair of wind turbine blades 511 a,b in an optimized orientationcombined with a second pair of wind turbine blades 511 a,b in a similaroptimized orientation with the pairs being arranged in an optimizedorientation as a single payload 511. Similarly, a second payloadarrangement 513 includes three wind turbine blades 513 a-c arrangedtogether and a third payload arrangement 514 includes two wind turbineblades 514 a,b arranged together. With regards to wind turbine sizes,FIG. 5A shows a straight single 90-meter wind turbine blade 501, a90-meter wind turbine blade 502 with a maximum pre-bend sweep angle, anda single 100-meter segmented wind turbine blade 503. Meanwhile, FIG. 5Bshows the first payload arrangement 511 including four 65-meter packagedwind turbine blades, the second payload arrangement 513 including three70-meter packaged wind turbine blades, and the third payload arrangement514 including two 85-meter packaged wind turbine blades.

In FIG. 5C, a space reservation 520 includes an inner surface 522 (e.g.,an initial keep-out zone) defined by the maximum extent of any portionoccupied by any of the representative cargo payloads and an outerportion 521 (e.g., a final keep-out zone) defined by one or more marginsapplied to the inner surface 522 to represent the minimum innerdimensions of a cargo bay configured to carry the representative cargopayloads.

Example Parametric Payload Model: Wind Turbine Blades

FIGS. 6A-6C are illustration of a parametric model of a wind turbineblade used to generate the representative payloads of FIGS. 5A and 5B.In this example parametric model of a desired potential payload, thegeneric wind turbine blade is parameterized by C_(m), Lc, L_(m), t_(m),b, v_(p), λ, and φ as either constants or single-term polynomials, asexplained in more detail below. Parametric models of a wind turbineblade allow an exhaustive family of turbine blades to be developed froma range of parameters.

Modern wind turbine blades have common features across the industry(even if details of those features vary across operating environmentsand manufacturer). Those common features include: (1) a cylindricalcross-section at the blade root location, and (2) a transition fromcylindrical cross-section to airfoil shape moving away from the bladeroot location along span.

Additionally, as wind turbine blades have become more efficient atgenerating power via lift while reducing mass, the loads have increasedand consequently deflection along the wind axial direction hasincreased. Just as in airplane wings, aeroelastic deflection leads to areduction in aerodynamic efficiency of the lifting surface. Tocounteract this shortcoming, blade designers have introduced pre-bend,which leads to the deformed shape of the blade to deviate less severelyfrom the desired shape compared to a blade without pre-bend. Additionalmeans of aeroelastic tailoring include twist of the airfoil along thespan and sweep (often referred to as pre-sweep). To this end, theparametric blade definition includes these bulk parameters.

The isometric view of the parameterized airfoil definition is shown inFIG. 6A. The inboard region begins at the root and includes the spanwisecoordinates up to the maximum chord spanwise coordinate L_(m). Theoutboard region begins at the maximum chord spanwise coordinate andincludes the remainder of the blade to the tip. The twist, denoted as φ,uses positive (right-hand) rotation about the x axis. Rotor rotation isdefined as counterclockwise for the blade trailing edge parallel to they-axis (blade coming out of the page). Consequently, pre-bend would beinto the opposite of rotor rotation, and the freestream wind fallsparallel to the y-axis.

The top-view of the parametric blade model is shown in FIG. 6B. Theairfoil at the maximum chord coordinate is at zero angle of attack withrespect to the XY plane (i.e., the trailing edge of the airfoil atmaximum chord is at z=0). The root axis of the blade is concentric withthe cylinder axis and orthogonal to its base on the YZ-plane, and thepre-bend and pre-sweep are measured with respect to it. The blade span,b, is also measured with respect to the root axis. The pre-sweep andpre-bend are denoted by the symbols λ and v_(p), respectively. The rootdiameter of the blade is d_(r) and is purely cylindrical for a distanceof L_(c) until a transition to the maximum chord airfoil, C_(m), whichis a location a spanwise distance L_(m) from the root.

Using the parametric model of FIG. 6A-C and estimates for the ranges ofeach parameters for representative payload sizes, a distribution ofindividual payload shapes can be generated and down-selected asnecessary to produce a representative population of payload objects.

Generating a Space Reservation

Once a representation population of payload objects is generated, groupsof multiple objects comprising a single payload must be packagedtogether, and then all single payloads must be positioned similarly inspace. Then, a number of different steps can be undertaken in differentorders to generate a homogenous volume from a plurality of individualvolumes, and these steps can occur in different orders: (1) taking aunion of all volumes, (2) sweeping either the union through ageneralized loading and unloading path or each the individual payloadvolume through a generalized loading and unloading path or a unique pathfor each payload, and (3) adding a plurality of margins to the union orto each individual payload volume. Notably, before any of these threesteps are undertaken, it may be useful to further down-select thepopulation of representative payloads in order to reduce thecomputational difficulty of generating the union.

The first step (1) involves overlaying a plurality of volumes, marginedor unmargined and swept or unwept, and generating a homogenous volumewith an outer surface formed by the outermost extent of each payloadvolume that does not reside inside any other volume. FIG. 7A is anisometric view of a plurality of overlapping representative cargopayloads, which are shown here as plurality of single wind turbineblades 702 a-j. The arrangement of FIG. 7A can be generated, forexample, by determining an optimal orientation of each payload objectwith respect to a hypothetical centerline of a cargo bay to, forexample, overlap each wind turbine blade 702 a-j such that thecombination represents a 3D volume containing each wind turbine blades702 a-j in a respective optimal arrangement. In other examples,groupings of payload objects can be included (e.g., two or more windturbine blades), where, in each grouping the individual payload objectsare arranged in an optimal orientation with respect to each other and,together, the group can be orientated in an optimal position withrespect to a hypothetical cargo centerline to be included in arepresentative group of payloads. Orientating each payload or payloadgroup in the plurality to a respective centerline enables, for example,aligning the centerline of each payload to form the group. FIG. 7B is anisometric view of a union of the plurality of overlapping representativecargo payloads of FIG. 7A. In FIG. 7B, the non-overlapping outervolumetric extent of each of the plurality of wind turbine blades 702a-j has been used to form a closed 3D geometric volume containing allthe wind turbine blades 702 a-j. This volume can be used as an initialkeep-out volume though, in some examples, this geometry can be furthersmoothed to generate a less convoluted shape for use in further steps.FIG. 7C shows an example homogenous union comprised of the plurality ofwind turbine blades 702 a-j and a wind turbine tower section 701overlaid with respect to the wind turbine blades 702 a-j. FIG. 7C alsoshows the resultant space reservation volume 720 that is generated afterall three steps are conducted.

FIGS. 8A-8E are supporting illustrations of the following discussion ofa plurality of different example margins that can be accounted for ingenerating a final keep-out volume. FIG. 8F is a schematic of eachmargin being added to a single representative payload volume or aninitial keep-out volume generated from a plurality of representativepayloads. Finally, FIG. 8G is a cross-sectional illustration of anexample aircraft fuselage showing representative payload disposed in anaircraft fuselage and cargo bay sized according to the space reservationshown in FIG. 8F.

Payloads often include figures that are used to both load the cargo inground static conditions, and to hold the cargo while the vehicle is inmotion and the generation of a space reservations can account for thesefixtures. FIG. 8A shows an example of a representative payload 810 thatincludes a fixture 810 c and a pair of wind turbine blades 810 a,b heldby that the fixture 810 c. for example when loading and/or unloading theblades 810 a, b. The fixture 810 c takes up additional space beyond thespace taken up by the wind turbine blades 810 a,b. Accordingly, in someembodiments, where the fixture size or volume is known, it can be addedto the representative payload volume before any additional steps areperformed. Alternatively, a fixture margin can be used to account for anexpected amount of space needed for any fixtures.

Large vehicles and their cargos or payloads can involve significantmanufacturing deviations as well. Generally, the difference in a vehicledesign and an actual manufactured vehicle may be different by fractionsof an inch, or even several inches for extremely large vehicles designedto carry cargos or payloads that are too large to be transported byother currently existing vehicles. FIG. 8B shows the representativepayload 810 of FIG. 8A disposed on a represented cargo loading/unloadingpath 820. This path 820 can be custom generated for the representativepayload 810 or it can be predetermined by several different aircraftconstraints, such as the kink angle discussed in view of FIG. 3A. With aknown path 820, the representative payload 810 is swept along the path820 to generate a swept volume 830 that represents the space needed tomove the representative payload 810 into and out of the hypotheticalcargo bay. The swept volume is the space occupied by the union of allpositions throughout a loading and/or unloading sweep. It is understoodthat the length of the swept volume 830 is significantly longer than anyanticipated cargo bay due, at least in part, to the necessity of alsohaving an opening to the cargo bay sufficient to unload and load thepayloads, and a possibility that the final length of the cargo bay is tobe determined using the result of this process, the entire swept volumecan be used during the space reservation process to size and position acargo bay opening around the swept volume.

Additionally, vehicles such as aircraft are frequently manufactured fromvarious aluminum alloys because of the beneficial strength properties ofthe alloys relative to their low density. Meanwhile, cargos or payloadsmight be made from generally different materials. Without providingpotentially heavy, expensive, fuel-thirsty payload bay environmentalcontrol systems (e.g., heat and pressurization), which may requiresignificant effort and schedule to develop and integrate, thedifferences in thermal expansion or contraction between the vehiclestructure and the payload or cargo can add up to several inches or evena few feet for large payloads and cargos. FIG. 8C illustrates an exampleof the differences between an as-designed wind turbine blade shape andsize 810 a, and an as-built wind turbine blade shape and size 810 a′.

Additionally, a space reservation can account for clearance between apayload or cargo in a vehicle, and the surrounding vehicle structure;otherwise, the relative motion that occurs during loading and unloadingoperations between these two flexible, potentially complex shapes canresult in a collision that may create, for example, vehicle and cargodamage and/or shipping delays. FIG. 8D illustrates an example of cargoor payload 840 indicated as Cylinder A and the available storage volume830 inside the aircraft fuselage is indicated by Cylinder B. Theindicated clearance margin 841 can accommodate the cargo/payload duringtransportation as well as during the loading/unloading process.

Finally, a space reservation can also be coupled with a structuraldefinition that can be necessary to support the vehicle shape underloads experienced due to the motion of the vehicle and the vehicle andpayload inertias during accelerations. FIG. 8E is an example of anaircraft fuselage section 850 with an interior cargo bay constructedfrom various structural elements. FIG. 8E shows a structural thicknesslocation 851 where a structural margin requirement can be used toapproximate the necessary thickness of the aircraft fuselage 850 aroundthe interior cargo bay. In the example of FIG. 8E, the structural ribsin the fuselage 850 are approximately 12 to 18 inches deep.Additionally, FIG. 8E illustrates landing gear wells 852 that alsooccupy space within the fuselage 850. A structural reservation margincan take into account all space limitations imposed by the design of theaircraft.

As shown in FIG. 8F, a plurality of different margins (e.g., additiveoffsets) may be brought together for each potential desired payloadshape 899 as a worst-case scenario to provide a space reservationoutside of which a vehicle shape may be defined. In FIG. 8F, thefollowing margins are illustrated:

A Nominal Payload Shape Uncertainty Margin 890: an additive offset forpotential unknown shape changes that a payload designer may make, beyondthe parametric model and parameter ranges that can be estimated togenerate the representative payload shapes. Basically, if the payloadshape changes in a way that is not foreseen, this initial margin canreduce the risk that such a change will materially affect the ability tobe transported. Example margins include approximately in the range ofabout 5% to about 10% of payload radius.

A Payload Manufacturing Tolerance Margin 891: an additive offset toaccount for manufacturing tolerances (i.e., it is rare, if notimpossible, to build something perfectly), and across multiplemanufacturing instances, locations, or tooling, it is expected that manypayloads will have defects and deviations in them. Example marginsinclude approximately in the range of about 0.125 inches to about 2inches of payload diameter and length.

A Payload Flexibility Margin 892: an additive offset to account forflexible payloads that can be expected to flex during aircraft maneuver,such as a rough landing and in-flight turbulence, and certain payloads(e.g., wind turbine blades) that are not expected to stay the sameshape. Accordingly, where a rigid payload shape may fit well, adeformable payload will likely require additional space to allow atemporary new shape to fit before the payload returns to the originalrigid shape. Additionally, some payloads may deform under their ownweight during loading and unloading and/or during flight. Examplemargins include approximately in the range of about 0 inches to about 12inches of payload diameter. In some embodiments, this margin can bereduced where it can be assumed that any subsequent clearances used forloading and/or unloading (which can be slow operations and do not implymuch flexibility) can be used as flexibility margins for a presumablystatic aircraft payload being loaded.

Thermal Expansion/Contraction Difference Margin 893: an additive offsetto account for the thermal expansion and contraction experienced by thepayload during transport. For example, wind turbine blades are generallymade of fiberglass or carbon fiber, wind turbine tower segments aregenerally made of steel, and a cargo aircraft fuselage is typically madeof aluminum. When a cargo aircraft starts out on the tarmac on a hot day(e.g., 120° F.), the aircraft and blades or towers may start at onesize, but when the aircraft and blades are at 43,000 feet, where thetemperature may be over 200° F. lower (e.g., −80° F.), the aircraft andblades or towers may be another size. This is at because materialsgenerally expand when they warm up, and contract when they cool down,but their expansion or contraction coefficient varies by material.Fiberglass and carbon fiber will grow or shrink much less than aluminum,for example. Accordingly, if a payload fits the cargo bay of a groundedaircraft on a hot day and then the aircraft shrinks relatively more thanthe payload at high altitude/lower temperature, this margin 893 isneeded to account for that difference. Moreover, because any expecteddifference is essentially a stretching rate this margin is particularlyimportant along the length direction of the aircraft. Example marginsinclude approximately in the range of about 0.125 inches to about 1 inchin diameter or height, and 1″ to 12″ in length.

A Holding Fixture Margin 894: an additive offset to account for fixturesand holding structures that are added to the payload shape to securelyload and unload the payload and/or stow the payload during transport.This margin can account for the uncertainly in future fixture designsand can alternatively be removed if the fixture shapes are included inthe payload models. Example margins include approximately in the rangeof about 12 inches to 24 inches.

A Loading/Unloading Sweep Margin 895: an additive offset to account forthe movement of the payloads when being loaded and unloaded. Especiallyfor more complicated aircraft cargo bay shapes (e.g., the “kinked”fuselage shape discussed above), and the fact that the fuselages oftentaper from front to back for aerodynamic reasons, the space needed forthe payload can vary as the payload is loaded and unloaded in ways thatare not obvious by just considering the final loaded shape. This margin895 can be accounted for in different ways. For example, as discussedabove, the starting payload geometry can be swept along one or moredifferent loading and unloading paths to generate a swept startingshape. In some instances, a margined payload can be swept in a similarmanner after one or more of the margins discussed herein are accountedfor. In other instances, a simpler additive offset is added across someor all of the payload shape where, for example, the loading andunloading paths are not yet determined. Example margins includeapproximately in the range of about 12 inches to about 36 inches.

A Clearance Margin 896: an additive offset to account for additionalspace between the payload and the fuselage. Typically, there needs to besome at least small amount of extra distance between the payload and thefuselage while the payload is moving relative to the fuselage. Thisdistance reservation margin 896 is the clearance. Example clearancemargins include approximately in the range of about 3 inches to about 24inches (e.g., 6 inches) and can vary depending, at least in part, on thetype of cargo and any associated regulations or other requirements, suchas the ability to walk around the payload during transport.

A Vehicle Manufacturing Tolerance Margin 897: an additive offset toaccount for the manufacturing tolerances of the interior of the cargobay, which has a nominal design shape, but an unknown as-built shape.While the difference between these two shapes is typically kept to somesmall amount (i.e., the stack-up of allowed tolerances on each of theindividual parts of the aircraft), some extra margin can be helpful.Example margins include approximately in the range of about 0.125 inchesto about 2 inches. With the accounting of this margin, a final keep outzone can be calculated as a summation of all the previous margins, whichrepresents a minimum cargo bay shape to carry the representedpayload(s).

A Vehicle Structural Frame Depth 898: in embodiments where an exteriorof the aircraft and/or an entire aircraft fuselage section is beingdesigned, this is an additive offset added to the “final keep out zone”to figure out how big a final lofted shape for the aircraft needs to be.This aircraft structure margin 898 accounts for the structural membersexpected to be found between the interior skin of the cargo bay and theexterior skin of the aircraft (e.g., frames, stringers, longerons,spars, ribs). These structural members can be extremely non-aerodynamicshapes, and they can take up space, which may require them to be outsideof the payload “final keep out zone” but inside of the aircraft skin.Example margins include approximately in the range of about 6 inches toabout 36 inches (e.g., approximately 18 inches), and may vary around thefuselage for example, being thicker below the payload to account for theweight of the payload being carried.

With each of the margins disclosed herein, any example or representativevalues are non-limiting, and a person skilled in the art will recognizethat some applications may result in margins that are above and/or belowthe exemplary ranges.

With the aircraft structure margin 898 added to the final keep out zone,a final exterior loft of the aircraft may be any desired aerodynamicshape 899 outside of that margined keep-out zone.

FIG. 8G shows a representative aircraft design result as across-sectional view of a fuselage section having an exterior andinterior cargo bay sized according to the space reservation margins ofFIG. 8F. In FIG. 8G, an exterior aircraft fuselage skin 899′ is loftedaccording to the minimum space dimensions determined by the finalexterior surface 899 of the space reservation. The fuselage also has aninterior cargo bay keep out zone 897′ that represents the minimuminterior dimensions of the cargo bay determined by the margined spacereservation up to the accounting for aircraft manufacturing tolerances.Further, a representative margined payload 894′ is disposed inside thefuselage to represent the largest accounted for margin of the actualpayload and fixtures during flight. In some examples, this can representa margined union of a population of representative payloads. Forexample, as determined by the parametric models discussed below.

FIG. 8H is an illustration of a translucent final keep-out volumeshowing an intermediate keep-out volume and a solid initial keep-outvolume. The initial keep-out volume is a 3D example of a desired payloadshape 899 that represents a group of different payloads in optimizedorientations. For the illustration of FIG. 8H, the initial keep-outvolume is presented as a simplified shape (i.e., smoothed exterior) toproduce a more realizable aircraft fuselage design. The intermediatekeep-out volume is formed from the initial keep-out volume with aplurality of margins, including and up to the clearance margin 896discussed above, which illustrates the maximum designed-for shape of apayload disposed in a cargo bay. Finally, the final keep-out volume isformed by adding the final margins, up to the aircraft skin 899, togenerate a 3D volume that can be used for sizing an exterior of anaircraft, as shown in FIG. 8I. FIG. 8I is an illustration of a solidfinal keep-out volume (e.g., the initial keep-out volume with margins upto and including the aircraft skin margin 899) disposed inside atranslucent exterior loft 900 of an actual aircraft design madeaccording to the size and shape of the final keep-out volume. Theexterior left 900 extends forward to account for a nose cone door, andupwards to include a cockpit, but generally the sizing of the aftwardexterior loft 900 following the final keep-out volume, with a fewacceptable deviations 899″ visible where, for example, an aerodynamic orstructural constraint may result in a small change from the finalkeep-out shape to meet other design constraints.

Parametric Payload Shape Modeling Systems and Methods

In order to design and build a vehicle that transports a specific cargo,a rigorous geometric definition of that cargo is helpful. In the absenceof clear design metrics of either current or anticipated future windturbine blade designs, systems and methods for generating a populationof representative payloads is described herein.

Both research and engineering judgment can be utilized to develop theparametrically defined geometry, as shown in FIGS. 6A-6C. The parametricmodel of the wind turbine blade can be used in the absence of actualspecifications and/or transportation requirements from wind turbineblade manufacturers. In addition to using this blade definition andenvelope for fuselage sizing and design, this data can be used in thedesign and analysis of an aircraft to promote consistency andcompatibility across the aircraft sub-systems.

A parametric model, such as the wind turbine blade definition discussedherein, can be created by researching various blade designs, designstudies, and wind turbine industry software that also requires asufficiently rigorous model definition. The parametric design space wasreduced by assuming a single airfoil and spanwise distribution ofvarious quantities. Most blade designs will have varying airfoilsections, and deviations of various parameters along the length of theturbine blade. However, for the purposes of a preliminary design, theeffect of these assumptions should be negligible while some amount ofmargin can be maintained based on an understanding of expectedvariances.

Approximating Design Trends

Data from a multitude of publicly available sources was compiled for asmany blade specifications as possible. Scatter plots were created fromthis data to extract correlations. A distribution of maximum chordlength (Cm) is plotted in FIG. 9A. A linear fit is shown to be a decentapproximation up to about 100 meters. Using the line fit illustrated inFIG. 9A, a 110-meter blade would yield a maximum chord of about 7meters, which was used as a maximum for this parametric model example.FIG. 9B shows the relationship of pre-bend v_(p) with blade length.Here, there is a significantly wider error band about this parameterthan the length-chord relationship. This risk was mitigated by usingsufficiently wide margins in the envelope creation for this parameter,discussed below. FIG. 9C illustrates the relationship of blade rootdiameter with blade length. Even accounting for an error band, thisparameter is not typically a controlling dimension for sizing anaircraft as compared to maximum chord length.

Together with design trends and engineering judgment, an uncertaintyrange can be assigned to each variable and each blade length. To reducethe total number of explicitly analyzed blade designs, in the presentinstance baseline values were assumed for maximum chord (C_(m)), rootdiameter (d_(r)), and thickness at max chord coordinate (t_(m)) for allthree different blade lengths: 85 meters, 90 meters, and a 110 metersegmented blade (e.g., two-part construction with a 70 meter rootsegment and a 40 meter tip segment). All three lengths assumed nominalvalues for both cylinder-root length (L_(c)) and length-to-max chordcoordinate (L_(m)). Additionally, a single airfoil and rationaldistributions for each parameter along the length of the blade can beused. While each blade design can have different spanwise distributionsfor each parameter, this is unlikely to influence the overall shapedesign of a fuselage. The resultant spanwise distributions used for thisexample parametric blade model definition are shown in FIG. 9D.

Payload Envelopes

In order to design the shape of the fuselage and the internal payloadspace reservations, an enveloping set of models can be generated usingthe parametric model applied to a plurality of different blade lengths.85-meter, 90-meter, and segmented 110-meter blades were used in thisexample. Uncertainty ranges for pre-bend, twist, and sweep at the bladetip can be assigned for all blade lengths for two primary reasons: a)these parameters govern the most out-of-plane spatial variation; and b)as blade lengths increase the aeroelastic loading is expected toincrease along with deflection, which is counteracted by bend, sweep,and/or twist.

A surface representation was created for each combination of parametersat the lower, nominal, and upper bounds of each range. FIGS. 10A-10Cillustrate different views of the geometric variations for a smallselection of the resultant 85-meter blade designs.

This process can be repeated for the 90-meter and 110-meter segmenteddesigns and the results can be combined and overlaid to generate anintermediate payload envelope for the parametric model. Thisintermediate payload envelopment is not anticipated to be a final outputof the process for at least two reasons: (1) not every payload object inthe result complete payload envelope actually extends or defines anouter limit of the envelop (i.e., a number of payload objects may lieentirely within another, larger payload object); and (2) theorientations of the payload objects are fixed, but the variousparameters considered can significantly change their effectiveorientation, as seen in FIG. 10A. Accordingly, a down-selection processcan used to reduce the number of total blade designs to analyze in thepackaging analysis. All blades for each length can be rotated 360degrees about the X-axis, and maximum Y and Z spatial spans can becomputed and ranked. Further, a subgroup of each length can be selectedand combined to provide a representative population of blade designsthat both maximizes and minimizes the out-of-axis spatial span. A finalpayload envelope can include as many expected future blade designs aspossible for the largest sizes the aircraft is intended to carry. Anoverlay of each blade of an example payload envelope after thedown-selection process is shown in FIG. 11 , including eight 85-meterblades 1101, four 90-meter blades 1102, and three 110-meter segmentedblades 1103.

While the above example has been conducted for wind turbine blades,other example payloads from which a parametric model can be generatedare suitable.

Payload Orientation Optimization Systems and Methods

Examples of the present disclosure include systems and methods ofcalculating optimized orientations of the generated population ofrepresentative payloads to maximize their packing efficiency beforegenerating an initial keep out volume for use with the sizing systemsand methods disclosed herein. In brief, when creating an initialkeep-out volume using payloads comprising multiple representativepayload objects, the overall efficiency of the final design can beimproved by only considering the payloads where the representativepayload objects are arranged in optimal orientations (e.g., ones thatminimize one or more cost functions, such as minimum clearance oroverall volume). Methods exist for determining one or more optimalarrangements to use. One such method is discussed below and more detailcan be found in International Patent Application No. PCT/US2020/049781,entitled “SYSTEMS AND METHODS FOR OPTIMIZATION OF PACKAGING LARGEIRREGULAR PAYLOADS FOR SHIPMENT BY AIR VEHICLES,” and filed Sep. 8,2020, the content of which is incorporated by reference herein in itsentirety.

Examples include routines for determining one or more optimized payloadconfigurations implemented using a computer processor executing asoftware program that takes, as an input, two or more objects (e.g.,wind turbine blades) each having a 3D surface geometry (or one iscalculated from a plurality of parameters defining the input object)that includes a large number of tessellated arbitrary surfaces. Theprogram can then execute one or more optimization routines thatsequentially perturb the orientation and position each 3D surfacegeometry through a large number of possible positions with respect toeach other (and, in some instances, a cargo bay volume). The program canfurther, for each position, calculate one or more cost functions and, asan output, return those orientations of each object for which thecalculated cost functions are one or more of minimized, maximized,within some predetermined threshold, and/or satisfies a similar type(s)of constraint.

In an exemplary embodiment, conventional software can be used to createthe tessellated 3D surface geometry for each object and, whenapplicable, for the interior of the cargo bay, which can be made upentirely of triangles or other arbitrary planar polygons. In anotheralternative embodiment, custom-written software can be used to createthe same tessellated 3D surface geometry for each object and, whenapplicable, for the interior of the cargo bay, which can be made upentirely of triangles or other arbitrary planar polygons. A finertessellation process requires more triangles to define the surface, butalso can result in a 3D surface geometry that more closely approximatesthe actual surface of the object being modeled. Accordingly, thefineness or resolution of the tessellation can depend on, for example, aparameter or cost function of the payload being calculated. Forinstance, if the cost function being calculated is a minimum clearancebetween each object of more than six (6) inches, it may be advantageousto have a 3D surface geometry that can vary less than a maximum of one(1) inch from the surface of the real object such that the maximumpossible variance between 3D surface geometries objects is four (4)inches on the corresponding real objects.

In operation, determining an optimal orientation of one or moreelongated irregular objects in space, such as wind turbine blades, canrequire numerous perturbations of each object in space and an evaluationof each minimum distance between the objects for clearance, as well asan evaluation of additional cost functions, such as volume or payloadcargo bay clearance.

FIG. 12A shows an example of two representative payload objects in anarbitrary orientation that can subsequently have their orientationsoptimized using aspects of the present disclosure to determine apackaging arrangement of the two payload objects that can satisfy one ormore cost functions, in addition to a simple clearance constraint (e.g.,they are not contacting or inside of each other). Specially, FIG. 12Ashows two wind turbine blades 1201, 1202 defining a payload arrangement1200, with each blade 1201, 702 being about 100 m long and occupyingabout 538.15 meters³ of volume, for a sum of 1,076.31 meters³ ofoccupied space of the blade combination. However, this payloadarrangement 1200 of wind turbine blades 1201, 1202 cannot nest perfectlytogether as illustrated because of their awkward, complex, irregularshapes. Moreover, there is no orientation or position of one windturbine blade relative to the other that results in zero gap distancesbetween one another over significant portions of their surfaces.Therefore, to package these wind turbine blades 1201, 1202 together andtransport them as a cargo payload 1200, they will require much moretotal volume to hold the package than the sum of the enclosed volume ofeach individual blade.

The output of the optimization routine can be one or more orientations,with the degrees of freedom of the orientation of each object beingshown in FIG. 12B for a wind turbine blade 1201, with each of the sixdegrees of freedom being: Roll (also referred to herein as ‘dRoll’),which is as angle of rotation about an X axis 1211, Pitch (also referredto herein as ‘dPitch’), which is an angle of rotation about a Y axis1213, Yaw (also referred to herein as ‘dYaw’), which is an angle about Zaxis 1212), Position along the X axis 1211 (also referred to herein asvariable ‘dX’), Position along the Y axis 1213 (also referred to hereinas ‘dY’), and Position along the Z axis 1212 (also referred to herein as‘dZ’), each of which can be varied for each object being positioned andorientated during the optimization routine. For each change in one ofthe six degrees of freedom for each object, the clearance is checkedand, if necessary, one or more cost functions are also checked. Aftereach orientation of each object has been checked, the output can be aplot that shows contours of cost functions versus orientation variables.In some situations, the absolute global minimum solution for a costfunction is not necessarily the best choice for the final orientation ofthe payload. However, the process described herein makes it simple toselect another configuration with marginally worse cost functionmagnitude but which is a better overall choice for other reasons. Insome instances, the range of each variable of one or more objects can beconstrained by one or more parameters, such as a maximum cargo baydimension (e.g., no object is translated to a position more than adifference between the overall length of the longest object and thecargo bay, as, for example, arranging two 100 meter objects in a 110meter long cargo bay requires that the other object not be translatedalong the axes closest approximating the 100 meter length by more than10 meters or so). Additionally, during the optimization, each degree offreedom can be incremented at a certain fineness or coarseness, whichcan determine the overall level of computation required. As such, it isalso possible to optimize the optimization routine by running itmultiple times, for example, using a first coarse increment to find afew orientations that satisfy the cost functions, and then re-runningthe routine with finer increments but with a range of the positions andorientation variables being roughly constrained about the known solutionregions to further determine the presence of local minimum and betteroptimize any global minimum. Alternatively, it is possible to automatesuch an approach using an adaptive algorithm which adds additionalsub-increments to each degree of freedom of each object near thelocations of the coarsely evaluated degree of freedom increments whichyielded the best cost function values.

The data generated by examples of the processes described herein allowfor quick and compact modeling of the resulting orientations in CADspace with only six (6) numbers (e.g., the degrees of freedomvariables). In some examples, for processing more than two wind turbineblades, it is possible to initiate the process by optimizing theorientation for two blades together, then optimize the third bladeagainst the “pre-packaged” pair of blades already optimized. For fourwind turbine blades, it is also possible to model the two pairsseparately and then optimize the pre-packaged pairs with respect to eachother. This is merely one option in the optimization process. It ispossible to model an arbitrary number of blades individually rather thanpre-packaged pairs. Those skilled in the art will appreciate that N=6variables are used for two blades, N=12 for three blades, N=18 for fourblades, and so forth. With a high-performance computing cluster, it ispossible run parallel processing sweeps through all orientations todetermine the optimal packaging.

In general, examples of the process disclosed herein can take anarbitrary number of tessellated arbitrary surfaces and execute a routineto output minimized cost function orientations, where the cost functionscan include, but are not limited to: (i) resultant payload volume (e.g.,the volume of the convex hull of a combination of the objections); (ii)unsigned distance from a set of entities (e.g., a cloud of points, aseries of line or curve segments, an additional arbitrary discrete oranalytical surface); and/or (iii) signed distance relative to a set ofentities (e.g., a cloud of points, a series of line or curve segments,an additional arbitrary discrete or analytical surface). One or more ofthese cost functions may be minimized within additional constraints,such as, for example, maintaining a minimum spatial clearance betweeneach arbitrary surface in the optimized package or restrictions onallowable orientation of each arbitrary surface in the optimizedpackage.

Examples of the present disclosure can therefore be used to analyzemultiple large, irregularly-shaped objects to determine how they may beoptimally oriented in space and/or in a predefined cargo bay volume, andoptimally subject to multiple constraints, to automatically optimize formultiple cost functions, such as to: (i) restrict predefined ranges oforientation; (ii) maintain a minimum clearance between objects in apayload; (iii) minimize an overall volume of the payload; (iv) minimizethe distance from the payload to a set of entities (e.g. orienting apayload as close as possible to a cargo centerline); and/or (v) maximizethe distance from the payload to to a set of entities (e.g., maintaininga minimum clearance between the payload and the cargo bay, or centeringthe payload within the cargo bay).

Examples include reducing the overall computational time of anoptimization process by restricting the ranges of orientations or theobjects. For example, it is not necessary to consider objectorientations where the longest dimension of one object is orthogonal tothe longest dimension of another object, as this orientation willobviously be unable to result in the optimal cost function of minimizingthe overall payload volume. Similarly, there are situations in whichobject symmetry implies that certain orientations do not need to beanalyzed because they are non-unique. Finally, there may be manufacturerrestrictions on certain object orientations during transportation,making it unnecessary to evaluate prohibited orientations.

In addition to optimizing the packaging of one or more objects, theprocess can evaluate orientations within the limitations of the internalvolume of the available cargo space (e.g., in the cargo bay of anaircraft). For example, a cargo bay may have “Keep Out” spaces where thepayload is not allowed to intrude. In one embodiment, the processdescribed herein can minimize the maximum distance from a curve alongthe cargo bay centerline to the furthest point outwards on the cargo. Inanother embodiment, the process described herein can maximize theminimum distance from aircraft structures in the cargo bay to thenearest point on the outside of the payload package to maintain as muchclearance as possible.

Examples of the systems and methods can start by creating geometricinputs (e.g., 3D surface geometries) for each object to be optimized asa payload. In some example processes this tessellation can occur as aninitial step, and may be outside of the optimizing routine, for example,using existing software solutions that may be external to the processesdiscussed herein. Additionally, this can include taking existing 3Dsurface geometries and adjusting or changing their properties, such astessellation density, to better execute the subsequent optimizationsteps. The example process continues with an input receiving parametersfor use during the optimization routine, for example one or moreallowable ranges of orientation for each object, minimum requiredclearance, additional desired cost functions, and/or increment size inperturbations of the objects. In some instances, the example processallows for preparation or modification of each 3D surface geometryduring or after this step, such that the subject optimizationcalculations can be processed more efficiently or quickly because the 3Dsurface geometry may be simplified without significantly impacting theaccuracy of the process beyond a fraction of the minimum requiredclearance.

The example process proceeds to an optimization routine in which theprocess can perturb each combination of every object through the fullrange of permitted orientations by the input increments in translationalong each spatial axis, and in rotation about each spatial axis. Ateach unique orientation, the minimum distance between each unique objectcan be checked against the minimum required clearance between allobjects, and other cost functions can be computed (e.g., total packagedvolume dimensions or convex hull volume, maximum unsigned distance fromentities including a series of points, curves, surfaces, and/or volumesinside of a cargo bay, and/or minimum signed distance from entitiesincluding a series of points, curves, surfaces, and/or volumes definingthe structural edges of a cargo bay). After the full range oforientations are analyzed, the process continues by outputting eachorientation that meets clearance and/or cost function constraints, alongwith cost function output, to allow selection from output of the optimumblade packaging (minimum cost function), or alternatively, a solutionthat is close to optimum but may meet additional constraints. Theoutputting can include storing the cost functions and/or calculatedclearances for each individually calculated orientation, or, in someinstances, storing each of the orientations and their corresponding costfunctions for orientations that satisfy one or more constraints on thecost functions or clearance. Implementations of this brute-forceoptimization approach to evaluating the entire orientation space can beextremely thorough (e.g., robust at finding global minimums to withinthe tolerance of the perturbation increments) and parallel (e.g.,allowing fully independent evaluation of each orientation in isolation).

In the example process, the optimization routine can include a series ofsteps defining each iteration in a single loop. The optimization routinecan include a check to see if all orientations have been consideredand/or if some desired optimized orientation has been achieved and, ifso, proceed to the output 940. The check can call an incrementer toadjust the position of one or more of the 3D surface geometries, andafterwards a geometric processor can determine one or more points on the3D surface geometries according to the cost functions (e.g., determiningthe closest two point between to objects). The result(s) can be sent toa comparer to calculate cost function values and cross-check any costfunction constraints with the values.

An example variation of these processes is a more complex solverapproach that determines sensitivities in each cost functions byperturbing the object orientations to determine a local minimum in costfunction at far fewer evaluated orientations.

Example Optimization Routine

It is difficult to show the plurality of nested loop of the exampleoptimization routines in a single flowchart, as there are six (6)variables to sweep through for each blade that is being oriented orpositioned relative to another blade and/or cargo bay shape.Accordingly, a pseudocode example is presented below for a two-objectoptimization loop (i.e., ‘Blade1’ and ‘Blade2’), with each layerrepresenting a nested loop adjusting one of the degrees of freedom arespective blade for each of the six degrees of freedom—dRoll (angleabout X axis in degrees), dPitch (angle about Y axis in degrees), dYaw(angle about Z axis in degrees), dX (position along X axis in inches),dY (position along Y axis in inches), and dZ (position along Z axis ininches)—which are varied. There can be a minimum and maximum valuechecked for each degree of freedom. For the angles, one example caninclude a full range that would be the bounds from spherical coordinates(e.g., dRoll, dYaw each being incremented from −180 deg to +180 deg, anddRoll from −90 deg to +90 deg), however, examples can include reductionsin these bounds being applied due to common sense, for example, that thepitch angle range will not exceed 50% above and below a fuselage kinkangle. For the lengths, a full range example would roughly thedifference in length between the primary dimensions of the blades andthe cargo bay, in each direction: for a 100 meter blade in a 105 meterfuselage, the blades may be taken forward and aft by five (5) metersfrom an intermediate position to cover the full range.

Routines can result in a substantial number of orientations beingcalculated. For example, if the number of calculations for each degreeof freedom is ten (10), the result is 10⁶ total permutations.Accordingly, it can be advantageous to limit the ranges of each degreeof freedom and use larger increments. Additionally, in examples thatinclude conducting a “packaging” step and a “place/orient payload invehicle” step separately, during the packaging step the one object canbe held static during an optimization routine. Then, once the best“payload package” of the objects relative to one another has beendetermined, a single 6-DOF sweep of a resultant packaged payload withinthe cargo bay with additional cost functions described above can beperformed. In algorithm parlance, this is replacing to get a lowernumber of permutations:

10¹² to optimize 3 blades+10⁶ to orient and position final bladepackage, which is substantially less than 10¹⁸ to simultaneously packageblades together and orient the blades in the cargo payload in a singleoptimization algorithm.

Example Cost Function: Minimum Clearance

Calculating the minimum clearance between each object ensures that aminimum amount of clearance can be maintained so that the objects do notdamage or touch one another in the finished packaging. During airtransport, for example, objects may undergo moderate verticalaccelerations (e.g., approximately in the range of about −1.0 G to about+2.5 G) and often continuous vibration. While example objects like windturbine blades are flexible items, and will deform small distances withloads, if they touch one another, they may abrade or forcefully collidein a way that leaves permanent, undesirable damage. By calculating amerit function of clearance, a filter may be applied to maintain aminimum amount of clearance, such as 6 inches between 100-meter-longwind turbine blades.

FIG. 13 is an illustration of the minimum clearance maintained byfiltering all permutations of six degrees of freedom between one blade1201 while a second blade 1202 is held static. In each orientation alarge number of individual inter-object clearances 1301 a-d arecalculated to determine a minimum 1302.

Example Optimized Payload and Aircraft

Using aspects of the present optimization method, including sweepingthrough six degrees of freedom for each object and repeating theprocess, testing each combination of the orientations of the two blades,an optimized arrangement can be found. This is shown, for example, inFIG. 14A, where an optimized payload arrangement 1470 of the first andsecond blades 1201, 1202 is illustrated in a highly efficient packagingorientation. To achieve this orientation, the top blade 1201 was rotated+176.5 degrees in the roll axis (about its longest dimension from rootto tip). Here, a 3D convex hull calculation results in only 42% wastedvolume relative to the minimum volume occupied by the combination of theindividual first and second blades 1201, 1202. This optimized payloadarrangement 1470 can be set as an initial keep out volume by itself andswept along a loading/unload path to generate a swept volume for use inthe aircraft sizing systems and methods disclosed herein. Additionally,or alternatively, the arrangement 1470 can be combined with one or moreother optimized arrangements of payload objects or individual pay loadobjects (which can be swept or unswept volumes) to create a spacereservation volume for use in sizing an aircraft cargo bay or the cargoaircraft fuselage section itself.

FIG. 14B shows the payload 1470 of FIG. 14A disposed in the interiorcargo bay 170 of the aircraft 100 of FIG. 1A. Here, the cargo bay 170 ofthe aircraft 100 was dimensioned according to a union of a plurality ofoptimized payload orientation and individual payload objects, includingthe optimized payload arrangement 1470. Accordingly, the cargo bay 170can allow the optimized payload arrangement 1470 to be loaded, unloaded,and stowed, as illustrated by FIG. 14B.

FIG. 15 is a block diagram of one exemplary embodiment of a computersystem 1500 upon which the present disclosures can be built, performed,trained, etc. For example, referring to FIGS. 7 to 14C, any modules orsystems can be examples of the system 1500 described herein, for examplethe optimization routines 900A, 900B and any of the associated modulesor routines described therein. The system 1500 can include a processor1510, a memory 1520, a storage device 1530, and an input/output device1540. Each of the components 1510, 1520, 1530, and 1540 can beinterconnected, for example, using a system bus 1550. The processor 1510can be capable of processing instructions for execution within thesystem 1500. The processor 1510 can be a single-threaded processor, amulti-threaded processor, or similar device. The processor 1510 can becapable of processing instructions stored in the memory 1520 or on thestorage device 1530. The processor 1510 may execute operations such asexecuting a parametric model to generate a population of representativepayload volumes, taking a union of one or more payload volumes, addingmargins to one or more payload volumes, generating a swept volume fromone or more payload volumes moving along a loading/unload path, and/orconducting an optimization routine on two or more payload objects todetermine optimized payload orientations, including calculating minimumclearance or other constraints, various cost functions and/or associatedconstraints, among other features described in conjunction with thepresent disclosure.

The memory 1520 can store information within the system 1500. In someimplementations, the memory 1520 can be a computer-readable medium. Thememory 1520 can, for example, be a volatile memory unit or anon-volatile memory unit. In some implementations, the memory 1520 canstore information related to wind turbine blades and cargo bays, costfunctions, and optimization landscapes, among other information.

The storage device 1530 can be capable of providing mass storage for thesystem 1500. In some implementations, the storage device 1530 can be anon-transitory computer-readable medium. The storage device 1530 caninclude, for example, a hard disk device, an optical disk device, asolid-date drive, a flash drive, magnetic tape, and/or some other largecapacity storage device. The storage device 1530 may alternatively be acloud storage device, e.g., a logical storage device including multiplephysical storage devices distributed on a network and accessed using anetwork. In some implementations, the information stored on the memory1520 can also or instead be stored on the storage device 1530.

The input/output device 1540 can provide input/output operations for thesystem 1500. In some implementations, the input/output device 1540 caninclude one or more of network interface devices (e.g., an Ethernet cardor an Infiniband interconnect), a serial communication device (e.g., anRS-232 10 port), and/or a wireless interface device (e.g., a short-rangewireless communication device, an 802.7 card, a 3G wireless modem, a 4Gwireless modem, a 5G wireless modem). In some implementations, theinput/output device 1540 can include driver devices configured toreceive input data and send output data to other input/output devices,e.g., a keyboard, a printer, and/or display devices. In someimplementations, mobile computing devices, mobile communication devices,and other devices can be used.

In some implementations, the system 1500 can be a microcontroller. Amicrocontroller is a device that contains multiple elements of acomputer system in a single electronics package. For example, the singleelectronics package could contain the processor 1510, the memory 1520,the storage device 1530, and/or input/output devices 1540.

Although an example processing system has been described above,implementations of the subject matter and the functional operationsdescribed above can be implemented in other types of digital electroniccircuitry, or in computer software, firmware, or hardware, including thestructures disclosed in this specification and their structuralequivalents, or in combinations of one or more of them. Implementationsof the subject matter described in this specification can be implementedas one or more computer program products, i.e., one or more modules ofcomputer program instructions encoded on a tangible program carrier, forexample a computer-readable medium, for execution by, or to control theoperation of, a processing system. The computer readable medium can be amachine-readable storage device, a machine-readable storage substrate, amemory device, a composition of matter effecting a machine-readablepropagated signal, or a combination of one or more of them.

Various embodiments of the present disclosure may be implemented atleast in part in any conventional computer programming language. Forexample, some embodiments may be implemented in a procedural programminglanguage (e.g., “C” or ForTran95), or in an object-oriented programminglanguage (e.g., “C++”). Other embodiments may be implemented as apre-configured, stand-along hardware element and/or as preprogrammedhardware elements (e.g., application specific integrated circuits,FPGAs, and digital signal processors), or other related components.

The term “computer system” may encompass all apparatus, devices, andmachines for processing data, including, by way of non-limitingexamples, a programmable processor, a computer, or multiple processorsor computers. A processing system can include, in addition to hardware,code that creates an execution environment for the computer program inquestion, e.g., code that constitutes processor firmware, a protocolstack, a database management system, an operating system, or acombination of one or more of them.

A computer program (also known as a program, software, softwareapplication, script, executable logic, or code) can be written in anyform of programming language, including compiled or interpretedlanguages, or declarative or procedural languages, and it can bedeployed in any form, including as a standalone program or as a module,component, subroutine, or other unit suitable for use in a computingenvironment. A computer program does not necessarily correspond to afile in a file system. A program can be stored in a portion of a filethat holds other programs or data (e.g., one or more scripts stored in amarkup language document), in a single file dedicated to the program inquestion, or in multiple coordinated files (e.g., files that store oneor more modules, sub programs, or portions of code). A computer programcan be deployed to be executed on one computer or on multiple computersthat are located at one site or distributed across multiple sites andinterconnected by a communication network.

Such implementation may include a series of computer instructions fixedeither on a tangible, non-transitory medium, such as a computer readablemedium. The series of computer instructions can embody all or part ofthe functionality previously described herein with respect to thesystem. Computer readable media suitable for storing computer programinstructions and data include all forms of non-volatile or volatilememory, media and memory devices, including by way of examplesemiconductor memory devices, e.g., EPROM, EEPROM, and flash memorydevices; magnetic disks, e.g., internal hard disks or removable disks ormagnetic tapes; magneto optical disks; and CD-ROM and DVD-ROM disks. Theprocessor and the memory can be supplemented by, or incorporated in,special purpose logic circuitry. The components of the system can beinterconnected by any form or medium of digital data communication,e.g., a communication network. Examples of communication networksinclude a local area network (“LAN”) and a wide area network (“WAN”),e.g., the Internet.

Those skilled in the art should appreciate that such computerinstructions can be written in a number of programming languages for usewith many computer architectures or operating systems. Furthermore, suchinstructions may be stored in any memory device, such as semiconductor,magnetic, optical, or other memory devices, and may be transmitted usingany communications technology, such as optical, infrared, microwave, orother transmission technologies.

Among other ways, such a computer program product may be distributed asa removable medium with accompanying printed or electronic documentation(e.g., shrink wrapped software), preloaded with a computer system (e.g.,on system ROM or fixed disk), or distributed from a server or electronicbulletin board over the network (e.g., the Internet or World Wide Web).In fact, some embodiments may be implemented in a software-as-a-servicemodel (“SAAS”) or cloud computing model. Of course, some embodiments ofthe present disclosure may be implemented as a combination of bothsoftware (e.g., a computer program product) and hardware. Still otherembodiments of the present disclosure are implemented as entirelyhardware, or entirely software.

One skilled in the art will appreciate further features and advantagesof the disclosures based on the provided for descriptions andembodiments. Accordingly, the inventions are not to be limited by whathas been particularly shown and described. For example, although thepresent disclosure provides for transporting large cargo, such as windturbines, the present disclosures can also be applied to other types oflarge cargo or to smaller cargo, at least some of which are mentionedabove. All publications and references cited herein are expresslyincorporated herein by reference in their entirety.

Examples of the Above-Described Embodiments can Include the Following

-   -   1. A method of generating a space reservation volume for use in        sizing a cargo bay of a cargo aircraft, the method comprising:        -   generating, using a processor, one or more optimized payload            orientations of one or more representative payloads to be            carried in a cargo bay of a cargo aircraft;        -   generating, using a processor, an initial keep out volume            containing the one or more optimized payload orientations;        -   creating, using a processor, a final keep out volume by            sequentially adding a plurality of margins to the initial            keep out volume; and        -   generating, using a processor, a space reservation volume            based on the final keep out volume, the space reservation            volume being dimensioned greater than or equal to the final            keep out volume such that the space reservation volume is            suitable for use in sizing interior dimensions of the cargo            bay and the cargo bay being suitable for at least one of            loading, unloading, or holding a payload represented by the            one or more representative payloads in their respective            optimized payload orientations.    -   2. The method of claim 1, wherein the one or more representative        payloads comprises one or more wind turbine blades.    -   3. The method of claim 1 or 2, wherein generating the initial        keep out volume comprises generating a union of 3D geometries of        the one or more optimized payload orientations.    -   4. The method of claim 1 or 2, wherein generating an initial        keep out volume comprises:        -   sweeping a 3D geometry of each of the one or more            representative payloads in their respective one or more            optimized payload orientations through at least one of a            simulated loading movement or a simulated unloading movement            to generate a swept 3D geometry of a volume swept through by            the one or more representative payloads; and        -   generating a union of the swept 3D geometries of the one or            more optimized payload orientations.    -   5. The method of any of claims 1 to 4, further comprising        generating one or more optimized payload orientations of two or        more representative payloads by running an optimization routine        configured to test a plurality of possible non-intersecting        orientations of the two or more representative payloads and        calculate at least one cost function for each possible        non-intersecting orientation, the optimized payload orientation        including a set of possible non-intersecting orientations that        at least one of: (1) minimizes the one or more cost functions;        or (2) minimizes a weighted average of the one or more cost        functions.    -   6. The method of claim 5, wherein running the optimization        routine to test the plurality of possible non-intersecting        orientations of the two or more representative payloads        comprises keeping a 3D geometry of at least one of the two or        more representative payloads fixed in space and sequentially        iterating a plurality of degrees of freedom of the 3D geometries        of the remaining two or more representative payloads and, for        each iteration, calculating the at least one cost function that        includes at least a minimum clearance between the two or more        representative payloads.    -   7. The method of any of claims 1 to 6, wherein the plurality of        margins comprises a first set of margins based on 3D geometries        of the one or more representative payloads.    -   8. The method of claim 7, wherein the first set of margins        comprises at least one or more of:        -   an additive offset for payload shape uncertainty;        -   an additive offset for payload manufacturing tolerances;        -   an additive offset for payload flexibility; or        -   an additive offset for thermal deformation.    -   9. The method of claim 7 or 8, wherein the plurality of margins        comprises a second set of margins based on 3D geometries of one        or more fixtures configured to hold the one or more        representative payloads in the one or more optimized payload        orientations, the second set including an additive offset for        the one or more fixtures.    -   10. The method of claim 9, wherein creating the final keep out        volume comprises creating an intermediate keep out volume by        sweeping the initial keep out volume through at least one of a        simulated loading movement or a simulated unloading movement to        generate a third set of margins of the plurality of margins        based on at least one of the loading or unloading sweeps, the        third set including an additive offset representing the volume        swept through by the intermediate keep out volume during the at        least one of the simulated loading movement or the simulated        unloading movement.    -   11. The method of claim 10, wherein creating the final keep out        volume comprises adding one or more of the first or second set        of margins to the initial keep out volume before sweeping the        initial keep out volume and subsequently adding the third set of        margins.    -   12. The method of claim 10, wherein creating the final keep out        volume comprises adding one or more of the first, second, or        third set of margins to the initial keep out volume after        sweeping the initial keep out volume.    -   13. The method of any of claims 10 to 12, wherein creating the        final keep out volume comprises adding a fourth set of margins        of the plurality of margins, the fourth set including an        additive offset representing a minimum clearance margin between        the intermediate keep out volume and an inner wall of the cargo        bay.    -   14. The method of claim 13, wherein the fourth set comprises an        additive offset representing manufacturing tolerances of the        cargo aircraft.    -   15. The method of claim 13 or 14, wherein the fourth set        comprises an additive offset representing structural elements        configured to support the one or more representative payloads in        the cargo bay.    -   16. The method of any of claims 13 to 15, wherein the fourth set        comprises an additive offset representing equipment configured        to move the one or more representative payloads during at least        one of a loading operation or an unloading operation.    -   17. The method of any of claims 13 to 16, wherein generating the        space reservation volume comprises generating a convex hull        based on the final keep out volume.    -   18. The method of any of claims 1 to 17, further comprising:        -   before generating the one or more optimized payload            orientations, calculating, using a processor, the one or            more representative payloads, the calculating including:            -   generating 3D geometries for a plurality of sample                payload shapes when a parameterized nominal payload                geometry definition comprises a plurality of geometric                parameters, each sample payload shape having at least                one different geometric parameter; and            -   reducing the plurality of sample payload shapes to the                one or more representative payloads using a                down-selection process to remove sample payload shapes                that do not expand a volume envelope of a combination of                all the sample payload shapes.    -   19. The method of claim 18, wherein generating 3D geometries for        a plurality of sample payload shapes comprises using a        parametric distribution of one or more of the plurality of        geometric parameters.    -   20. The method of claim 18 or 19, wherein the parameterized        nominal payload geometry comprises a parameterized nominal wind        turbine geometry.    -   21. The method of claim 20, wherein the plurality of geometric        parameters include one or more of the following:        -   a blade twist angle;        -   an airfoil shape;        -   a blade span length;        -   a root diameter;        -   a cylindrical root length;        -   a root transition length;        -   a maximum chord length;        -   a location of the maximum chord length;        -   a thickness at the location of the maximum chord length;        -   a pre-bend tip deflection; or        -   a pre-sweep tip deflection.    -   22. The method of any of claims 1 to 21, further comprising        generating a plurality of dimensions for use in sizing a cargo        bay structure to contain the space reservation volume.    -   23. The method of any of claims 1 to 22, further comprising        generating a plurality of dimensions for use in sizing a cargo        aircraft fuselage structure to at least one of contain, load, or        unload the space reservation volume.    -   24. A computer system, comprising:    -   an optimization module configured to generate one or more        optimized payload orientations of one or more representative        payloads to be carried in a cargo bay of a cargo aircraft;        -   a generating module configured to generate an initial keep            out volume containing the one or more optimized payload            orientations;        -   a margining module configured to create a final keep out            volume by sequentially adding a plurality of margins to the            initial keep out volume; and        -   a designing module configured to generate a space            reservation volume based on the final keep out volume, the            space reservation volume being dimensioned greater than or            equal to the final keep out volume such that the space            reservation volume is suitable for use in sizing interior            dimensions of the cargo bay and the cargo bay being suitable            for at least one of loading, unloading, or holding a payload            represented by the one or more representative payloads in            their respective optimized payload orientations.    -   25. The computer system of claim 24, wherein the one or more        representative payloads comprises one or more wind turbine        blades.    -   26. The computer system of claim 24 or 25, wherein the        generating module is further configured to generate the initial        keep out volume by generating a union of 3D geometries of the        one or more optimized payload orientations.    -   27. The computer system of claim 24 or 25, wherein the        generating module is further configured to generate an initial        keep out volume by:        -   sweeping a 3D geometry of each of the one or more            representative payloads in their respective one or more            optimized payload orientations through at least one of a            simulated loading movement or a simulated unloading movement            to generate a swept 3D geometry of a volume swept through by            the one or more representative payloads; and        -   generating a union of the swept 3D geometries of the one or            more optimized payload orientations.    -   28. The computer system of any of claims 24 to 27, wherein the        optimization module is further configured to generate one or        more optimized payload orientations of two or more        representative payloads by running an optimization routine        configured to test a plurality of possible non-intersecting        orientations of the two or more representative payloads and        calculate at least one cost function for each possible        non-intersecting orientation, the optimized payload orientation        including a set of possible non-intersecting orientations that        at least one of: (1) minimizes the one or more cost functions;        or (2) minimizes a weighted average of the one or more cost        functions.    -   29. The computer system of claim 28, wherein running the        optimization routine to test the plurality of possible        non-intersecting orientations of the two or more representative        payloads comprises keeping a 3D geometry of at least one of the        two or more representative payloads fixed in space and        sequentially iterating a plurality of degrees of freedom of the        3D geometries of the remaining two or more representative        payloads and, for each iteration, calculating the at least one        cost function that includes at least a minimum clearance between        the two or more representative payloads.    -   30. The computer system of any of claims 24 to 29, wherein the        plurality of margins comprises a first set of margins based on        3D geometries of the one or more representative payloads.    -   31. The computer system of claim 30, wherein the first set of        margins comprises at least one or more of:        -   an additive offset for payload shape uncertainty;        -   an additive offset for payload manufacturing tolerances;        -   an additive offset for payload flexibility; or an additive            offset for thermal deformation.    -   32. The computer system of claim 30 or 31, wherein the plurality        of margins comprises a second set of margins based on 3D        geometries of one or more fixtures configured to hold the one or        more representative payloads in the one or more optimized        payload orientations, the second set including an additive        offset for the one or more fixtures.    -   33. The computer system of claim 32, wherein the margining        module is further configured to create the final keep out volume        by creating an intermediate keep out volume by sweeping the        initial keep out volume through at least one of a simulated        loading movement or a simulated unloading movement to generate a        third set of margins of the plurality of margins based on at        least one of the loading or unloading sweeps, the third set        including an additive offset representing the volume swept        through by the intermediate keep out volume during the at least        one of the simulated loading movement or the simulated unloading        movement.    -   34. The computer system of claim 33, wherein the margining        module is further configured to create the final keep out volume        by adding one or more of the first or second set of margins to        the initial keep out volume before sweeping the initial keep out        volume and subsequently adding the third set of margins.    -   35. The computer system of claim 33, wherein the margining        module is further configured to create the final keep out volume        by adding one or more of the first, second, or third set of        margins to the initial keep out volume after sweeping the        initial keep out volume.    -   36. The computer system of any of claims 33 to 35, wherein the        margining module is further configured to create the final keep        out volume by adding a fourth set of margins of the plurality of        margins, the fourth set including an additive offset        representing a minimum clearance margin between the intermediate        keep out volume and an inner wall of the cargo bay.    -   37. The computer system of claim 36, wherein the fourth set        comprises an additive offset representing manufacturing        tolerances of the cargo aircraft.    -   38. The computer system of claim 36 or 37, wherein the fourth        set comprises an additive offset representing structural        elements configured to support the one or more representative        payloads in the cargo bay.    -   39. The computer system of any of claims 36 to 38, wherein the        fourth set comprises an additive offset representing equipment        configured to move the one or more representative payloads        during at least one of a loading operation or an unloading        operation.    -   40. The computer system of any of claims 36 to 39, wherein the        designing module is further configured to the create space        reservation volume by generating a convex hull based on the        final keep out volume.    -   41. The computer system of any of claims 24 to 40, further        comprising:        -   a modeling module, configured to, before generating the one            or more optimized payload orientations, calculate the one or            more representative payloads, the modeling module being            configured to:            -   generate 3D geometries for a plurality of sample payload                shapes when a parameterized nominal payload geometry                definition comprises a plurality of geometric                parameters, each sample payload shape having at least                one different geometric parameter; and            -   reduce the plurality of sample payload shapes to the one                or more representative payloads using a down-selection                process to remove sample payload shapes that do not                expand a volume envelope of a combination of all the                sample payload shapes.    -   42. The computer system of claim 41, wherein the modeling module        is further configured to generate 3D geometries for a plurality        of sample payload shapes by using a parametric distribution of        one or more of the plurality of geometric parameters.    -   43. The computer system of claim 41 or 42, wherein the        parameterized nominal payload geometry comprises a parameterized        nominal wind turbine geometry.    -   44. The computer system of claim 43, wherein the plurality of        geometric parameters include one or more of the following:        -   a blade twist angle;        -   an airfoil shape;        -   a blade span length;        -   a root diameter;        -   a cylindrical root length;        -   a root transition length;        -   a maximum chord length;        -   a location of the maximum chord length;        -   a thickness at the location of the maximum chord length;        -   a pre-bend tip deflection; or        -   a pre-sweep tip deflection.    -   45. The computer system of any of claims 24 to 44, wherein the        designing module is further configured to generate a plurality        of dimensions for use in sizing a cargo bay structure to contain        the space reservation volume.    -   46. The computer system of any of claims 24 to 45, wherein the        designing module is further configured to generate a plurality        of dimensions for use in sizing a cargo aircraft fuselage        structure to at least one of contain, load, or unload the space        reservation volume.    -   47. A computer program product, comprising a tangible,        non-transient computer usable medium having computer readable        program code thereon, the computer readable program code        comprising program code configured to:        -   generate one or more optimized payload orientations of one            or more representative payloads to be carried in a cargo bay            of a cargo aircraft;        -   generate an initial keep out volume containing the one or            more optimized payload orientations;        -   create a final keep out volume by sequentially adding a            plurality of margins to the initial keep out volume; and        -   generate a space reservation volume based on the final keep            out volume, the space reservation volume being dimensioned            greater than or equal to the final keep out volume such that            the space reservation volume is suitable for use in sizing            interior dimensions of the cargo bay and the cargo bay being            suitable for at least one of loading, unloading, or holding            a payload represented by the one or more representative            payloads in their respective optimized payload orientations.    -   48. The computer program product of claim 47, wherein the one or        more representative payloads comprises one or more wind turbine        blades.    -   49. The computer program product of claim 47 or 48, wherein the        instructions to generate the initial keep out volume comprises        instruction to generate a union of 3D geometries of the one or        more optimized payload orientations.    -   50. The computer program product of claim 47 or 48, wherein the        instructions to generate an initial keep out volume comprises        instructions to:        -   sweep a 3D geometry of each of the one or more            representative payloads in their respective one or more            optimized payload orientations through at least one of a            simulated loading movement or a simulated unloading movement            to generate a swept 3D geometry of a volume swept through by            the one or more representative payloads; and        -   generate a union of the swept 3D geometries of the one or            more optimized payload orientations.    -   51. The computer program product of any of claims 47 to 50,        further comprising the instructions to generate one or more        optimized payload orientations of two or more representative        payloads by running an optimization routine configured to test a        plurality of possible non-intersecting orientations of the two        or more representative payloads and calculate at least one cost        function for each possible non-intersecting orientation, the        optimized payload orientation including a set of possible        non-intersecting orientations that at least one of: (1)        minimizes the one or more cost functions; or (2) minimizes a        weighted average of the one or more cost functions.    -   52. The computer program product of claim 51, wherein in        instructions to run the optimization routine to test the        plurality of possible non-intersecting orientations of the two        or more representative payloads comprises instructions to keep a        3D geometry of at least one of the two or more representative        payloads fixed in space and sequentially iterate a plurality of        degrees of freedom of the 3D geometries of the remaining two or        more representative payloads and, for each iteration,        calculating the at least one cost function that includes at        least a minimum clearance between the two or more representative        payloads.    -   53. The computer program product of any of claims 47 to 52,        wherein the plurality of margins comprises a first set of        margins based on 3D geometries of the one or more representative        payloads.    -   54. The computer program product of claim 53, wherein the first        set of margins comprises at least one or more of:        -   an additive offset for payload shape uncertainty;        -   an additive offset for payload manufacturing tolerances;        -   an additive offset for payload flexibility; or        -   an additive offset for thermal deformation.    -   55. The computer program product of claim 53 or 54, wherein the        plurality of margins comprises a second set of margins based on        a 3D geometries of one or more fixtures configured to hold the        one or more representative payloads in the one or more optimized        payload orientations, the second set including an additive        offset for the one or more fixtures.    -   56. The computer program product of claim 55, wherein the        instructions to create the final keep out volume comprises        instructions to create an intermediate keep out volume by        sweeping the initial keep out volume through at least one of a        simulated loading movement or a simulated unloading movement to        generate a third set of margins of the plurality of margins        based on at least one of the loading or unloading sweeps, the        third set including an additive offset representing the volume        swept through by the intermediate keep out volume during the at        least one of the simulated loading movement or the simulated        unloading movement.    -   57. The computer program product of claim 56, wherein the        instructions to create the final keep out volume comprises the        instructions to add one or more of the first or second set of        margins to the initial keep out volume before sweeping the        initial keep out volume and subsequently adding the third set of        margins.    -   58. The computer program product of claim 56, wherein the        instructions to create the final keep out volume comprises the        instructions to add one or more of the first, second, or third        set of margins to the initial keep out volume after sweeping the        initial keep out volume.    -   59. The computer program product of any of claims 56 to 58,        wherein the instructions to create the final keep out volume        comprises the instructions to add a fourth set of margins of the        plurality of margins, the fourth set including an additive        offset representing a minimum clearance margin between the        intermediate keep out volume and an inner wall of the cargo bay.    -   60. The computer program product of claim 59, wherein the fourth        set comprises an additive offset representing manufacturing        tolerances of the cargo aircraft.    -   61. The computer program product of claim 59 or 60, wherein the        fourth set comprises an additive offset representing structural        elements configured to support the one or more representative        payloads in the cargo bay.    -   62. The computer program product of any of claims 59 to 61,        wherein the fourth set comprises an additive offset representing        equipment configured to move the one or more representative        payloads during at least one of a loading operation or an        unloading operation.    -   63. The computer program product of any of claims 59 to 62,        wherein the instructions to generate the space reservation        volume comprises the instructions to generate a convex hull        based on the final keep out volume.    -   64. The computer program product of any of claims 47 to 63,        further comprising:        -   before the instructions to generate the one or more            optimized payload orientations, instructions to calculate            the one or more representative payloads, the instructions            including:            -   instructions to generate 3D geometries for a plurality                of sample payload shapes when a parameterized nominal                payload geometry definition comprises a plurality of                geometric parameters, each sample payload shape having                at least one different geometric parameter; and            -   instructions to reduce the plurality of sample payload                shapes to the one or more representative payloads using                a down-selection process to remove sample payload shapes                that do not expand a volume envelope of a combination of                all the sample payload shapes.    -   65. The computer program product of claim 64, wherein the        instructions to generate 3D geometries for a plurality of sample        payload shapes comprises instructions to use a parametric        distribution of one or more of the plurality of geometric        parameters.    -   66. The computer program product of claim 64 or 65, wherein the        parameterized nominal payload geometry comprises a parameterized        nominal wind turbine geometry.    -   67. The computer program product of claim 66, wherein the        plurality of geometric parameters include one or more of the        following:        -   a blade twist angle;        -   an airfoil shape;        -   a blade span length;        -   a root diameter;        -   a cylindrical root length;        -   a root transition length;        -   a maximum chord length;        -   a location of the maximum chord length;        -   a thickness at the location of the maximum chord length;        -   a pre-bend tip deflection; or        -   a pre-sweep tip deflection.    -   68. The computer program product of any of claims 47 to 67,        further comprising instructions to generate a plurality of        dimensions for use in sizing a cargo bay structure to contain        the space reservation volume.    -   69. The computer program product of any of claims 47 to 68,        further comprising instructions to generate a plurality of        dimensions for use in sizing a cargo aircraft fuselage structure        to at least one of contain, load, or unload the space        reservation volume.    -   70. An aircraft, comprising:        -   a fuselage defining a forward end, an aft end, a cargo bay            that spans a majority of a length of the fuselage from the            forward end to the aft end the interior cargo bay defining            an interior volume of a size and shape determined by:            -   generating one or more optimized payload orientations of                one or more representative payloads to be carried in the                cargo bay;            -   generating an initial keep out volume containing the one                or more optimized payload orientations;            -   creating a final keep out volume by sequentially adding                a plurality of margins to the initial keep out volume;                and            -   generating the interior volume based on the final keep                out volume, the size and shape of the interior volume                being dimensioned greater than or equal to the final                keep out volume such that the interior volume of the                cargo bay is suitable for at least one of loading,                unloading, or holding a payload represented by the one                or more representative payloads in their respective                optimized payload orientations.

What is claimed is:
 1. A method of generating a space reservation volume for use in sizing a cargo bay of a cargo aircraft, the method comprising: generating, using a processor, one or more optimized payload orientations of one or more representative payloads to be carried in a cargo bay of a cargo aircraft; generating, using a processor, a keep out volume containing the one or more optimized payload orientations, the generating including: sweeping a 3D geometry of each of the one or more representative payloads in their respective one or more optimized payload orientations through at least one of a simulated loading movement along a known path or a simulated unloading movement along the known path to generate a swept 3D geometry of a volume swept through by the one or more representative payloads; and generating a union of the swept 3D geometries of the one or more optimized payload orientations as the keep out volume; and generating, using a processor, a space reservation volume based on the keep out volume, the space reservation volume being dimensioned greater than or equal to the keep out volume such that the space reservation volume is suitable for use in sizing interior dimensions of the cargo bay and the cargo bay being suitable for at least one of loading, unloading, or holding a payload represented by the one or more representative payloads in their respective optimized payload orientations.
 2. The method of claim 1, wherein the one or more representative payloads comprises one or more wind turbine blades.
 3. The method claim 1, further comprising generating one or more optimized payload orientations of two or more representative payloads by running an optimization routine configured to test a plurality of possible non-intersecting orientations of the two or more representative payloads and calculate at least one cost function for each possible non-intersecting orientation, the optimized payload orientation including a set of possible non-intersecting orientations that at least one of: (1) minimizes the one or more cost functions; or (2) minimizes a weighted average of the one or more cost functions.
 4. The method of claim 3, wherein running the optimization routine to test the plurality of possible non-intersecting orientations of the two or more representative payloads comprises keeping a 3D geometry of at least one of the two or more representative payloads fixed in space and sequentially iterating a plurality of degrees of freedom of the 3D geometries of the remaining two or more representative payloads and, for each iteration, calculating the at least one cost function that includes at least a minimum clearance between the two or more representative payloads.
 5. The method of claim 1, further comprising, sequentially adding a plurality of margins to the keep out volume and/or the 3D geometries of the one or more representative payloads before generating the space reservation.
 6. The method of claim 5, wherein a first set of margins comprises at least one or more of: an additive offset for payload shape uncertainty; an additive offset for payload manufacturing tolerances; an additive offset for payload flexibility; or an additive offset for thermal deformation.
 7. The method of claim 5, wherein the plurality of margins comprises a second set of margins based on 3D geometries of one or more fixtures configured to hold the one or more representative payloads in the one or more optimized payload orientations, the set including an additive offset for the one or more fixtures.
 8. The method of claim 7, wherein creating the keep out volume comprises adding one or more of the first or second set of margins to the each 3D geometry of the one or more representative payloads before sweeping the 3D geometries.
 9. The method of claim 1, wherein generating the space reservation volume comprises generating a convex hull based on the keep out volume.
 10. The method of claim 1, further comprising: before generating the one or more optimized payload orientations, calculating, using a processor, the one or more representative payloads, the calculating including: generating 3D geometries for a plurality of sample payload shapes when a parameterized nominal payload geometry definition comprises a plurality of geometric parameters, each sample payload shape having at least one different geometric parameter; and reducing the plurality of sample payload shapes to the one or more representative payloads using a down-selection process to remove sample payload shapes that do not expand a volume envelope of a combination of all the sample payload shapes.
 11. The method of claim 10, wherein generating 3D geometries for a plurality of sample payload shapes comprises using a parametric distribution of one or more of the plurality of geometric parameters.
 12. The method of claim 10, wherein the parameterized nominal payload geometry comprises a parameterized nominal wind turbine geometry.
 13. The method of claim 12, wherein the plurality of geometric parameters include one or more of the following: a blade twist angle; an airfoil shape; a blade span length; a root diameter; a cylindrical root length; a root transition length; a maximum chord length; a location of the maximum chord length; a thickness at the location of the maximum chord length; a pre-bend tip deflection; or a pre-sweep tip deflection.
 14. A computer system, comprising: a modeling module, configured to calculate one or more representative payloads to be carried in a cargo bay of a cargo aircraft, the modeling module being configured to: generate 3D geometries for a plurality of sample payload shapes based on a parameterized nominal payload geometry nominal wind turbine geometry definition comprising a plurality of geometric parameters, each sample payload shape having at least one different geometric parameter; and reduce the plurality of sample payload shapes to the one or more representative payloads using a down-selection process to remove sample payload shapes that do not expand a volume envelope of a combination of all the sample payload shapes; an optimization module configured to generate one or more optimized payload orientations of the one or more representative payloads; a generating module configured to generate a keep out volume containing the one or more optimized payload orientations; and a designing module configured to generate a space reservation volume based on the keep out volume, the space reservation volume being dimensioned greater than or equal to the keep out volume such that the space reservation volume is suitable for use in sizing interior dimensions of the cargo bay and the cargo bay being suitable for at least one of loading, unloading, or holding a payload represented by the one or more representative payloads in their respective optimized payload orientations.
 15. The computer system of claim 14, wherein the generating module is further configured to generate the keep out volume by generating a union of 3D geometries of the one or more optimized payload orientations.
 16. The computer system of claim 14, wherein the generating module is further configured to generate keep out volume by: sweeping a 3D geometry of each of the one or more representative payloads in their respective one or more optimized payload orientations through at least one of a simulated loading movement along a known path or a simulated unloading movement along the known path to generate a swept 3D geometry of a volume swept through by the one or more representative payloads; and generating a union of the swept 3D geometries of the one or more optimized payload orientations.
 17. The computer system of claim 16, wherein the known path comprises a bend based on at least a predetermined kink angle of the aircraft.
 18. The computer system of claim 14, wherein the optimization module is further configured to generate one or more optimized payload orientations of two or more representative payloads by running an optimization routine configured to test a plurality of possible non-intersecting orientations of the two or more representative payloads and calculate at least one cost function for each possible non-intersecting orientation, the optimized payload orientation including a set of possible non-intersecting orientations that at least one of: (1) minimizes the one or more cost functions; or (2) minimizes a weighted average of the one or more cost functions.
 19. The computer system of claim 14, further comprising a margining module configured to sequentially add a plurality of margins to the keep out volume before generating the space reservation.
 20. The computer system of claim 19, wherein a first set of the plurality of margins comprises at least one or more of: an additive offset for payload shape uncertainty; an additive offset for payload manufacturing tolerances; an additive offset for payload flexibility; or an additive offset for thermal deformation.
 21. The computer system of claim 19, wherein the margining module is further configured to margin the keep out volume by sweeping by sweeping each of the one or more representative payloads in their one or more optimized payload orientations through at least one of a simulated loading movement or a simulated unloading movement to generate a second set of margins of the plurality of margins based on at least one of the loading or unloading sweeps, the second set including an additive offset representing the volume swept through by each of the one or more representative payloads during the at least one of the simulated loading movement or the simulated unloading movement.
 22. The computer system of claim 21, wherein the margining module is further configured to margin the keep out volume by adding one or more of the first set of margins to each of the each of the one or more representative payloads before sweeping the each of the one or more representative payloads and subsequently adding the second set of margins.
 23. The computer system of claim 14, wherein the designing module is further configured to the create space reservation volume by generating a convex hull based on the keep out volume.
 24. The computer system of claim 14, wherein the optimization module is configured to determine optimal orientations of each sample payload shape from the modeling module, and wherein the modeling module is configured to reduce the plurality of sample payload shapes based on the optimal orientations.
 25. The computer system of claim 14, wherein the parameterized nominal payload geometry comprises a parameterized nominal wind turbine geometry.
 26. A computer program product, comprising a tangible, non-transient computer usable medium having computer readable program code thereon, the computer readable program code comprising program code configured to: generate one or more optimized payload orientations of one or more representative payloads to be carried in a cargo bay of a cargo aircraft; generate a keep out volume containing the one or more optimized payload orientations by: sweeping a 3D geometry of each of the one or more representative payloads in their respective one or more optimized payload orientations through at least one of a simulated loading movement along a known path or a simulated unloading movement along the known path to generate a swept 3D geometry of a volume swept through by the one or more representative payloads, and generating a union of the swept 3D geometries of the one or more optimized payload orientation; and generate a space reservation volume based on the keep out volume, the space reservation volume being dimensioned greater than or equal to the keep out volume such that the space reservation volume is suitable for use in sizing interior dimensions of the cargo bay and the cargo bay being suitable for at least one of loading, unloading, or holding a payload represented by the one or more representative payloads in their respective optimized payload orientations.
 27. The computer program product of claim 26, wherein the known path comprises a bend based on at least the fuselage kink angle of the aircraft.
 28. An aircraft, comprising: a fuselage defining a forward end, an aft end, a cargo bay that spans a majority of a length of the fuselage from the forward end to the aft end the interior cargo bay defining an interior volume of a size and shape determined by: generating one or more optimized payload orientations of one or more representative payloads to be carried in the cargo bay; generating a keep out volume containing the one or more optimized payload orientations by: sweeping a 3D geometry of each of the one or more representative payloads in their respective one or more optimized payload orientations through at least one of a simulated loading movement along a known path or a simulated unloading movement along the known path to generate a swept 3D geometry of a volume swept through by the one or more representative payloads, and generating a union of the swept 3D geometries of the one or more optimized payload orientations; and generating the interior volume based on the keep out volume, the size and shape of the interior volume being dimensioned greater than or equal to the keep out volume such that the interior volume of the cargo bay is suitable for at least one of loading, unloading, or holding a payload represented by the one or more representative payloads in their respective optimized payload orientations.
 29. The aircraft of claim 28, wherein the fuselage defines a fuselage kink angle of the aft end with respect to the forward end, and the known path comprises a bend based on at least the fuselage kink angle of the aircraft. 